Python: Jupyter intermediate
Technology:
Expertise:
- 11 Courses | 14h 1m 46s
- 10 Books | 62h
- 39 Courses | 20h 39m
- 11 Books | 55h 49m
- Includes Lab
- 6 Courses | 9h 40m 34s
- 8 Books | 41h 15m
- 1 Course | 1h 16m 54s
- 2 Courses | 2h 18m 8s
- 6 Courses | 7h 49m
- 5 Books | 34h 45m
- Includes Lab
- 5 Courses | 5h 52m 8s
- 8 Books | 24h 46m
- 12 Courses | 11h 47m 34s
- 10 Books | 69h 30m
- Includes Lab
- 11 Courses | 14h 21m 28s
- 5 Books | 25h 36m
- Includes Lab
- 4 Courses | 6h 16m 25s
- 6 Courses | 3h
- Includes Lab
- 2 Courses | 2h 54m 9s
- 1 Course | 1h 32m 19s
- 2 Courses | 3h 1m 5s
- 5 Courses | 6h 56s
- 5 Courses | 6h 9m 46s
- 2 Courses | 3h 40m 3s
Explore Python, the general purpose high-level programming language focused on code readability and efficiency.
GETTING STARTED
IT Infrastructure Automation: Python Automation Programming
-
3m 5s
-
7m 23s
GETTING STARTED
Python Development: Getting Started with Programming in Python
-
2m 3s
-
6m 17s
GETTING STARTED
Flask in Python: An Introduction to Web Frameworks & Flask
-
2m 3s
-
9m 13s
GETTING STARTED
Building Web Apps Using Django: Introduction to Web Frameworks & Django
-
2m 2s
-
8m 20s
GETTING STARTED
Excel with Python: Working with Excel Spreadsheets from Python
-
2m 5s
-
4m 9s
GETTING STARTED
Python Design Patterns: Principles of Good Design
-
2m 11s
-
6m 3s
GETTING STARTED
Web Applications with Django: Introducing the Django Web Framework
-
2m 57s
-
9m
GETTING STARTED
Flask in Python: User Interactions in Flask Applications
-
2m 6s
-
5m 32s
GETTING STARTED
Dash Python Framework: Dash for Interactive Web Apps
-
2m 6s
-
11m 3s
GETTING STARTED
Developing Apps with Tkinter: Getting Started
-
2m 18s
-
6m 8s
GETTING STARTED
Dash Python Framework: Leveraging Dash with User Input & Dash DataTable
-
2m 19s
-
10m 39s
COURSES INCLUDED
IT Infrastructure Automation: Python Automation Programming
Explore Python and how Python can be used to create and manage automation in an IT environment.
15 videos |
1h 36m
Assessment
Badge
Python - Introduction to Pandas and DataFrames
Simplify data analysis with Pandas DataFrames. Pandas is a Python library that enables you to work with series and tabular data, including initialization, and population. For this course, learners do not need prior experience working with Pandas, but should be familiar with Python3, and Jupyter Notebooks. Topics include the following: Define your own index for a Pandas series object; load data from a CSV (comma separated values) file, to create a Pandas DataFrame; Add and remove data from your Pandas DataFrame; Analyze a portion of your DataFrame; Examine how to reshape or reorient data, and to create a pivot table. Finally, represent multidimensional data in two-dimensional DataFrames, with multi or hierarchical indexes.
14 videos |
1h 4m
Assessment
Badge
Python - Manipulating & Analyzing Data in Pandas DataFrames
Explore advanced data manipulation and analysis with Pandas DataFrames, a Python library that shares similarities with relational databases. To take this course, prior basic experience is needed with Pandas DataFrames, data loading, and Jupyter Notebook data manipulation. You will learn to iterate data in your DataFrame. See how to export data to Excel files, JSON (JavaScript Object Notation) files, and CSV (comma separated values) files. Sort the contents of a DataFrame and manage missing data. Group data with a multi-index. Merge disparate data into a single DataFrame through join and concatenate operations. Finally, you will determine when and where to integrate data with structured queries, similar to SQL.
10 videos |
44m
Assessment
Badge
Conditional Statements & Loops: If-else Control Structures in Python
Learners will explore implementations of the order of precedence of operators, using if-elif-else statements to evaluate multiple conditions and conversions between various data types in Python, in this 15-video course. Key concepts covered here include how conditions in Python work, and how to evaluate conditions by involving primitive data types using if statements and complex data types using if statements. Next, evaluate multiple conditions for decision making with nested control structures; identify how to use the if-else statement to make decisions involving complex data types such as lists, tuples, and dictionaries; and learn how to convert an integer to a float and a float or an integer to a string, and vice-versa. Learners then observe how to convert primitive data types to complex data types, to convert between various complex data types, and to convert between various complex data types and view base conversions with Python built-in functions; and to solve various programming problems with Python built-in methods. Finally, you will learn to solve various programming problems by using if-elif-else statements and nested if-else statements.
15 videos |
1h 40m
Assessment
Badge
Conditional Statements & Loops: The Basics of for Loops in Python
Loops are one way to perform the same operations repeatedly in a program. For loops are the control structure to use when the repeated operations are performed on a sequence such as a list or a tuple. In this 9-video course, you will explore different ways to iterate over a sequence using for loops. Key concepts covered in this course include how to use for loops to process elements in a list and characters in a string; and how to code for loops to iterate over values in a tuple and the keys and values in a dictionary. Next, learn the function of associating an else block with a Python for loop; include if-else statements and other for loops within a for loop; how to generate a sequence of consecutive integers with the range function; and how to use the range function to iterate over a large range of values and apply it within nested for loops. Finally, observe how to write for loops in order to iterate over 1-dimensional and 2-dimensional sequences.
9 videos |
1h 1m
Assessment
Badge
Conditional Statements & Loops: Advanced Operations Using for Loops in Python
Explore how iterating over elements using for loops can be controlled using the break and continue statements in Python. Creating sequences from other sequences using comprehensions is also covered in this 9-video course. Key concepts covered here include how to terminate a for loop when a specific condition is met using the break statement; learning how the break statement affects the code in the else block of a for loop; and observing how to skip an iteration of a for loop when a specific condition is met using the continue statement. Next, learn how to use the continue statement along with the break statement within the same for loop; learn the fact that no action is performed under specific conditions by using the pass statement; and create a list out of the contents of another list using a comprehension. Finally, you will learn about conditions in list comprehensions in order to filter elements used in the source list and to define values in the newly created list.
9 videos |
1h 5m
Assessment
Badge
Conditional Statements & Loops: While Loops in Python
While loops are one way to keep repeating a set of actions until a specific condition is met in Python. In this 11-video course, learners explore the use of while loops, considerations when implementing while loops, and use cases for while loops and for loops. Key concepts covered here include implementing a basic while loop and recognizing what conditions cause it to become an infinite loop; learning to use while loops to carry out actions while evaluating expressions based on numerical and string data; and examining while loops whose iterations depend on user input data. Next, learn syntax for defining while loops within a single line; learn to iterate over a list of elements with while loops; and learn to iterate over multiple lists and tuples with while loops. Learn when it is appropriate to use break keyword to stop a while loop, and learn to break out of a while loop and recognize use of the pass keyword within such loops. Finally, learn skip steps in individual iterations of a while loop using the continue statement.
11 videos |
1h 19m
Assessment
Badge
Python Concurrent Programming: Introduction to Concurrent Programming
Explore the general theory of concurrent programming, and examine how to have multiple tasks active at any given point in time. This 14-video course offers an in-depth examination of concurrent programming by using the Python programming language. First, learners will examine the two main forms of concurrent programming, multithreading and multiprocessing, and examine their differences and use cases. Next, you will examine executing multitask sequentially, and with multithreading to save time, and how to use multiprocessing to manage a collection of tasks efficiently. Continue by exploring challenges that programmers encounter when adopting concurrency such as synchronization issues and deadlocks, and how to address these issues. You will examine issues that arise when writing concurrent code, and you will learn how to fix these by using the built-in objects available in Python. Finally, this course examines several of the objects available in the Python language such as queues and pools, which simplify the task of building multithreading and multiprocessing applications.
14 videos |
1h 29m
Assessment
Badge
Python Concurrent Programming: Multithreading in Python
This course offers an in-depth exploration of the creation and management of concurrent threads in Python. In its 14 videos, you will learn how to significantly improve the performance and responsiveness of your apps by using concurrent threads. Begin by examining how threads are created in Python from their initialization to their execution; then learn how to use the various synchronization mechanisms such as locks, semaphores, and events. Next, you will examine how concurrent execution could occur in two ways: multithreading and parallel. You will learn to use multithreading to run chunks of each task at one time, and then switch between them regularly. You will learn multiprocessing of threads by executing tasks in parallel. Learners will examine concurrent execution of threads, and some of the issues that arise when these threads are not synchronized. Finally, you will examine several threads of synchronization mechanisms available in Python such as locks, semaphores, events, and conditions and explore the properties and use cases for each of these objects.
14 videos |
1h 41m
Assessment
Badge
Python Concurrent Programming: Multiprocessing in Python
This course is a lab-only exploration of the creation and management of processes in Python to speed up the execution of your programs. In this 10-video course, learners will use Jupyter notebooks to execute all programs demonstrated. First, you will learn how to create initialized threads, and how to do the same with processes in Python. Then you will examine different thread-safe data structures in Python to implement queues, stacks, and priority queues. Next, you will learn how to use Python for synchronization mechanisms and inter-process communication, and will see a comparison of processes to threads. You will learn to use Python's built-in queue data structure for multithreaded applications, and how to implement multiprocessing. Continue by learning how processes are created and executed and how they differ from threads when one is using shared resources. You will explore how to use a manager class, or service process manager to share any Python types. Finally, you will examine the available mechanisms in Python for communication and synchronization between processes.
10 videos |
1h 16m
Assessment
Badge
Python Concurrent Programming: Asynchronous Executions in Python
This 9-video course offers a lab-only exploration and introduction to the libraries available in Python to run tasks asynchronously by using both processes and threads. To take this course, you should have prior knowledge of how to spawn and manage processes in Python. First, you will learn how to significantly improve the performance and responsiveness of your application by running them concurrently, then learn how to create a process pool, and how to use multiprocessing to execute tasks in parallel. Next, you will learn to use multithreading to run chunks of a task at one time, and to switch between the chunks regularly. Learners will then examine the concurrent.futures module, which contains objects to run threads and processes in an asynchronous manner, and to monitor their progress while they are still executing. Continue by learning how to use ThreadPoolExecutor, available in the concurrent.futures module. Finally, you examine the asyncio module in Python, which provides lightweight mechanisms for asynchronous executions of tasks.
9 videos |
1h 1m
Assessment
Badge
SHOW MORE
FREE ACCESS
COURSES INCLUDED
New Developments in Python
Python is an easy to learn, easy to read programming language widely used in scripting and application development. It's flexible and interpretive nature provides immediate feedback to users, making it one of the most popular programming languages today. Explore the roots of the Python language and discover its significant features. Examine the differences between versions 2 and 3 of Python and the process of migrating to the newer version. Delve into the new features that have been packed into subsequent releases of Python 3 and see how these can be adopted to build better applications. Finally, learn some of the best practices when it comes to building applications with Python - from the right syntax to improve readability to making your code easy to extend.
7 videos |
46m
Assessment
Badge
Getting Started with Python: Introduction
This 15-video course lets learners explore the basics of how to use the Python programming language. You will learn to set up with an interactive environment that allows you to develop and run Python scripts on your machine. Begin by installing Anaconda, an open-source distribution of the Python and R programming languages. You will learn to write your first meaningful program in Python, then create a Jupyter notebook, the most popular tool for writing and running Python code. You will learn how to do simple coding by using Python's Jupyter notebooks, and explore different Jupyter functionalities, including built-in functions. Learners will explore how to use a Python variable to store values, and learn to differentiate between variables of different types, and the different ways to assign values to variables. You will examine how variables act as containers, and you will learn how to change values that are inside a container. Finally, you will learn to use integers, floating-point numbers, strings, and to work with Boolean values.
15 videos |
1h 30m
Assessment
Badge
Complex Data Types in Python: Working with Lists & Tuples in Python
Learn how to work with lists, tuples, and strings in Jupyter notebook in Python in this 14-video course. You will discover similarities and differences between tuples and lists and see how strings are essentially just a list of characters. Begin with an introduction to lists, and then create and initialize lists in Python. You will then access and update list elements; add, remove, sort, and reverse elements from a list; execute built-in functions with lists, and create new lists from existing lists by using slicing operations. Next, examine how to extract specific elements from the original list using step size; perform list functions on strings; invoke functions on the string object; and access substrings with slicing operations. Receive an introduction to tuples, exploring the similarities between lists and tuples, then move on to understanding tuple immutability by specifying differences between lists and tuples. Then an introduction to other complex data types and using dictionaries and sets in Python. The concluding exercise concerns recalling differences and similarities between lists and tuples.
14 videos |
1h 39m
Assessment
Badge
Complex Data Types in Python: Working with Dictionaries & Sets in Python
This 9-video course helps learners explore dictionary data type in Python. Dictionaries are associative containers used to store key-value pairs. Given a key, finding the associated value is optimized by Python to be extremely efficient. First, receive an introduction to dictionaries in Jupyter Notebook in Python. You will learn how to create and initialize dictionaries, then learn about nesting complex data types within dictionaries. Continuing with the study of Python dictionaries, you will explore what functions and methods can be invoked on these dictionaries, such as modifying and updating dictionaries using dictionary methods. Next, you will be introduced to sets, another commonly used complex data type that Python supports. You will then create and initialize sets. This leads on to performing set operations such as union, intersection difference, and other set operations. You will also examine nested lists, and work with nested types within other complex data types. In the final tutorial, you will learn how to convert lists to dictionaries and vice versa. The concluding exercise entails recalling features of dictionaries and sets.
9 videos |
53m
Assessment
Badge
Complex Data Types in Python: Shallow & Deep Copies in Python
Explore copying operations on containers in Python in this 9-vdeo course, which examines the subtle distinction between shallow and deep copies. Changes made to shallow copies affect the original whereas with deep copies they do not. Learners begin by observing Jupyter notebook in Python, where you will be performing shallow and deep copies of Python strings. You will learn how to create shallow copies of lists, and then create deep copies of lists where changes to the copy do not affect the original. Following this, you will begin working with tuples, a process which you will discover is quite simple because tuples are immutable. So you will learn how to create shallow and deep copies of tuples. You will also learn how deep copies of dictionaries work, and perform shallow and deep copies of sets. In the closing exercise, learners are asked to recall how shallow and deep copies work for complex data types.
9 videos |
44m
Assessment
Badge
Conditional Statements & Loops: If-else Control Structures in Python
Learners will explore implementations of the order of precedence of operators, using if-elif-else statements to evaluate multiple conditions and conversions between various data types in Python, in this 15-video course. Key concepts covered here include how conditions in Python work, and how to evaluate conditions by involving primitive data types using if statements and complex data types using if statements. Next, evaluate multiple conditions for decision making with nested control structures; identify how to use the if-else statement to make decisions involving complex data types such as lists, tuples, and dictionaries; and learn how to convert an integer to a float and a float or an integer to a string, and vice-versa. Learners then observe how to convert primitive data types to complex data types, to convert between various complex data types, and to convert between various complex data types and view base conversions with Python built-in functions; and to solve various programming problems with Python built-in methods. Finally, you will learn to solve various programming problems by using if-elif-else statements and nested if-else statements.
15 videos |
1h 40m
Assessment
Badge
Conditional Statements & Loops: The Basics of for Loops in Python
Loops are one way to perform the same operations repeatedly in a program. For loops are the control structure to use when the repeated operations are performed on a sequence such as a list or a tuple. In this 9-video course, you will explore different ways to iterate over a sequence using for loops. Key concepts covered in this course include how to use for loops to process elements in a list and characters in a string; and how to code for loops to iterate over values in a tuple and the keys and values in a dictionary. Next, learn the function of associating an else block with a Python for loop; include if-else statements and other for loops within a for loop; how to generate a sequence of consecutive integers with the range function; and how to use the range function to iterate over a large range of values and apply it within nested for loops. Finally, observe how to write for loops in order to iterate over 1-dimensional and 2-dimensional sequences.
9 videos |
1h 1m
Assessment
Badge
Conditional Statements & Loops: Advanced Operations Using for Loops in Python
Explore how iterating over elements using for loops can be controlled using the break and continue statements in Python. Creating sequences from other sequences using comprehensions is also covered in this 9-video course. Key concepts covered here include how to terminate a for loop when a specific condition is met using the break statement; learning how the break statement affects the code in the else block of a for loop; and observing how to skip an iteration of a for loop when a specific condition is met using the continue statement. Next, learn how to use the continue statement along with the break statement within the same for loop; learn the fact that no action is performed under specific conditions by using the pass statement; and create a list out of the contents of another list using a comprehension. Finally, you will learn about conditions in list comprehensions in order to filter elements used in the source list and to define values in the newly created list.
9 videos |
1h 5m
Assessment
Badge
Conditional Statements & Loops: While Loops in Python
While loops are one way to keep repeating a set of actions until a specific condition is met in Python. In this 11-video course, learners explore the use of while loops, considerations when implementing while loops, and use cases for while loops and for loops. Key concepts covered here include implementing a basic while loop and recognizing what conditions cause it to become an infinite loop; learning to use while loops to carry out actions while evaluating expressions based on numerical and string data; and examining while loops whose iterations depend on user input data. Next, learn syntax for defining while loops within a single line; learn to iterate over a list of elements with while loops; and learn to iterate over multiple lists and tuples with while loops. Learn when it is appropriate to use break keyword to stop a while loop, and learn to break out of a while loop and recognize use of the pass keyword within such loops. Finally, learn skip steps in individual iterations of a while loop using the continue statement.
11 videos |
1h 19m
Assessment
Badge
Functions in Python: Introduction
Explore how Python facilitates code reuse by using functions in this 17-video course, which shows learners how to define functions, learn passing arguments to functions, and returning values from functions. The functions you will examine change the state of the program, may have side effects, and have observable effects other than their return values. Since functions with side effects are hard to parallelize and use in a distributed environment, you will learn correct ways of returning values from functions. First, you will learn how to invoke functions by using both positional and keyword arguments. You will next work with positional input arguments in custom functions, and learn that these are required arguments, and how to order these arguments to invoke your function. You will next learn to use variable length arguments in defining custom functions. Finally, you will learn how keyword arguments or named arguments are a way to make the intent behind function invocation absolutely explicit, and help prevent bugs in programs that are especially hard to detect.
17 videos |
2h 3m
Assessment
Badge
Functions in Python: Gaining a Deeper Understanding of Python Functions
This 13-video course offers learners an in-depth exploration of Python functions, by focusing on nuances such as argument passing by value and reference, and local and global variables. In this course, you will examine how functions are first-class citizens in Python, as with other data types. You will examine how Python allows functions to be stored in variables, passed into other functions as arguments, and returned from functions as return values. Next, you will learn how to identify and apply differences between parsing arguments by value and reference. Examine how Python treats functions on par with other data types, a key attribute of a program seeking to support the functional programming paradigm; and learn how to work with use and throw functions by using lam das. This course then covers how lightweight functions for one-off use called lambda functions or anonymous functions play an important role in keeping Python code both succinct and readable. Finally, you will learn how to appropriately choose between local and global variables for use in your program.
13 videos |
1h 25m
Assessment
Badge
Functions in Python: Working with Advanced Features of Python Functions
This course explores advanced Python function topics such as recursion, closures, and using generator functions to generate sequences. In 12 videos, you will learn how to use decorators to add functionality to code; examine how recursion can be used to construct code to solve complex problems; and learn to write a terminating condition for a recursive function. Next, you will learn how to use an Iterator to respond to a built-in next () function. Learners will also examine closures, and how as functions they maintain their own lexical environment; and explore how closures are functions that can yield dramatic results in the distributed processing of code, and are widely used in the implementation of distributed processing frameworks. Then you will learn how to use generator functions to generate sequences. You will learn how sequences can iterated upon by other parts of your program. Finally, you will learn that using decorators offers simple ways of invoking higher-order functions.
12 videos |
1h 26m
Assessment
Badge
Data Structures & Algorithms in Python: Fundamental Data Structures
Explore Python data structures and delve into the details of some of the basic structures, such as linked lists, stacks, and queues. Key concepts covered in this 12-video course include the metrics on which algorithms and operations on data are evaluated; learning how the performance of operations and algorithms is expressed in terms of size of input; and learning about linked lists and their contents and structure. Next, study different ways in which nodes can be added to a linked list and how search operations work on this data structure; learn methods to remove nodes from a linked list and the process of reversing the order of nodes in this data structure; and learn techniques used to keep track of numbers of elements in linked lists. You will examine workings of a stack data structure, including the addition and removal of elements; learn some of the operations on stacks, such as ISEMPTY and ISFULL, and the complexities of different stack operations; and learn the queue data structure and how to compare it to stacks.
12 videos |
1h 19m
Assessment
Badge
Data Structures & Algorithms in Python: Implementing Data Structures
Examine operations that have different values of time complexity and delve into implementation of basic data structures, such as linked lists, stacks, and queues in Python, in this 13-video course. Key concepts covered here include operations that run in constant time regardless of input; code whose time complexity varies directly with value of input; and tasks whose time complexity varies linearly with size of input. Next, you will learn about operations whose time complexity varies as the square of input size; how to use native queue class of Python and perform standard queue operations; and how to code a queue class for many standard queue operations, such as enqueue and dequeue. Then, learn how a Python list can be used as a stack by loading and unloading elements, and how to implement a custom stack class for common stack operations. Finally, study code functions to perform search and delete operations in linked lists and reverse the ordering of its nodes; and create a linked list and test out various operations that have been defined.
13 videos |
1h 29m
Assessment
Badge
Data Structures & Algorithms in Python: Sorting Algorithms
In this 11-video course, learners explore workings of some of the most widely used sorting algorithms in Python and examine how their performance affects various measures. Key concepts covered here include various properties of sorting algorithms when selecting the right one for your data; the operations involved when sorting a list of values by using the selection sort algorithm; and the process of a bubble sort when applied to a list of values. Next, you will learn about the performance of the bubble sort on various measures such as time, space, and number of swaps; how to describe the steps involved in performing an insertion sort and compare it to the bubble sort; and learn the workings of the shell sort and the performance metrics of this divide and conquer algorithm. Finally, you will learn the process of sorting a list of elements using merge sort and list the complexity of this algorithm on various measures; and learn how the quicksort algorithm partitions and sorts a list of elements.
11 videos |
1h 14m
Assessment
Badge
Data Structures & Algorithms in Python: Implementing Sorting Algorithms
Examine the Python implementation of common sorting algorithms such as selection sort, bubble sort, and insertion sort, as well as divide and conquer sorts such as shell sort, merge sort, and quicksort, in this 10-video course. Key concepts covered in this course include how to write the code to implement a selection sort; how to implement the bubble sort algorithm in Python; and how to code a function to implement the insertion sort algorithm. Next, you will observe how to write the code to implement the divide-and-conquer shell sort algorithm; how to invoke the shell sort algorithm on an array of integers and examine the output at each iteration to understand how it works; and how to code a function to implement the merge sort algorithm and test it on an array of integers. Finally, learn how to write the partition and quicksort functions in order to implement a quicksort; and how to apply quicksort on an array of integers and analyze the results at each iteration to understand how the algorithm works.
10 videos |
1h 10m
Assessment
Badge
Data Structures & Algorithms in Python: Trees & Graphs
This 13-video course explores the theory of graph and tree data structures in Python. Learners will examine a specific type of tree: the binary search tree, its structures and properties. You will then observe how to execute common tasks in binary tree; examine the binary search algorithm; and review data structures of linked lists, stacks, and queues. Next, learners will examine how a binary tree structure offers several applications that cannot be done by using stacks or queues. The course demonstrates different depth first traversals, including pre-order, in-order traversals, and post-order traversals. Explore graphs, which are data structures used to model relationships, and different representations of a graph, and learn to model a vertex. Learners continue by observing how to represent an adjacency list as a graph, and examining the adjacency matrix, the adjacency list, and the adjacency set. Then you will explore graph traversal algorithms, including the topological sort. Finally, learn how to traverse through each of the vertices in a graph.
13 videos |
1h 32m
Assessment
Badge
Data Structures & Algorithms in Python: Implementing Trees & Graphs
Explore implementing trees and graphs in Python in this 14-video, hands-on course that contains only labs. In this course, learners will use Python 3 and Jupyter Notebooks as their IDE (integrated development environment). In the course labs, you will implement a binary search, define a binary search tree, and use code functions to work with those data structures. Next, you will implement algorithms to traverse trees, including how to perform a breadth-first traversal and depth-first traversal of the tree. Continue by examining graph data structure, and implementing different representations of graphs in Python by using an abstract class for a graph to represent graphs as both an adjacency set and an adjacency matrix. You will implement algorithms to traverse such graphs, including a breadth-first traversal and a depth-first traversal. This course then demonstrates how to run a test to check its implementation. Finally, learners observe how to implement a topological sort for a specific type of graph which is both directed as well as acyclic.
14 videos |
1h 25m
Assessment
Badge
Python Basics
Python is a very popular choice among professional developers for writing computer applications. In this course, you'll discover the basic features of Python, beginning with an overview of the Python language. Then you'll explore how to install Python and learn its basic syntax. You'll learn how to use variables with strings and how to save Python files, flow control, conditionals, comparisons, loops, and lists. You'll go on to how to use loops and lists, implement flow control in an application, and obtain user input. You'll discover functions in Python, Boolean and None data types, and custom functions. You'll learn about Python and JSON modules, file handlers, and how to use exception handling to solve problems. You'll discover the Python package manager (pip), Python Package Index, and the benefits of reusing libraries in Python programming. Finally, you'll discover HTTP requests, APIs, and dictionary data types in Python programming. This course was originally created by Global Knowledge (GK).
37 videos |
1h 7m
Assessment
Badge
Python Requests: HTTP Requests with Python
Learners can explore how to use the Python Request package which has simplified the task of constructing HTTP requests in this 16-video lab course, which explores different types of HTTP requests, and examines several ways to handle responses to those requests. Begin by learning how to use the Python request package to make a GET request for data from a server. Then you will observe how to construct a POST request to submit data to a host, and how to send it to a URL. Continue by learning how to use a HEAD request to check the resource information before downloading it by using GET, and how to examine request and response headers. Next, learners will examine a PUT request which has the same effect whether one makes the request once or multiple times, and which is used to overwrite an existing resource. You will learn to use DELETE requests. Finally, you will learn to address responses to requests in both JSON formatted or images.
16 videos |
1h 42m
Assessment
Badge
Socket Programming in Python: Introduction
Learners can explore basic concepts of Python socket programming, and how to communicate small amounts of data between Python applications by using either the same machine or over a network, in this 9-video course. Begin by learning how to use Python language to set up a communication line by creating a socket. Then learn to initialize a simple socket, and use it to transfer text data from one application to another. This course next demonstrates how to create a client app and server app in Python, and how each app uses a socket to communicate. Learners will observe a demonstration of how to transmit a Python dictionary and custom object over a socket connection. You will learn how to use a socket model to set up a simple TCP (transmission control protocol) socket to transfer text between applications. Next, learners will examine other properties of Python sockets, including its use with the context manager and the setting of a time-out for connections. Finally, you will learn to use the Pickle library to convey Python objects over a socket connection.
9 videos |
1h 2m
Assessment
Badge
Socket Programming in Python: Advanced Topics
This 11-video course explores advanced features of Python sockets, including the transfer of large files over sockets, two-way communication, and differences between blocking and nonblocking sockets. You will learn to transfer large files over sockets by breaking them up into chunks, and to transfer images over TCP (transmission control protocol) sockets. Then you will learn how to transfer Python objects by using the pickle module. Next, learn how to create a chat application and use it to transfer several types of data from a server application to a client. Learners continue by exploring how to configure two-way communication over sockets by building a simple chat. This course examines the performance versus reliability trade-off when one uses blocking and nonblocking sockets. You will examine and compare TCP, a connection-oriented protocol, and UDP (Universal Datagram Protocol) which is connectionless. Finally, you will examine the performance versus reliability trade-off with a TCP and UDP, and why TCP is better suited for apps which require high reliability at the other end of the communication line.
11 videos |
1h 20m
Assessment
Badge
Security Programming: Python Scripting Essentials
Python is ubiquitous in modern desktop, server, and cloud computing environments. The ability to identify when to use Python, along with a working knowledge of how to write and run a Python script, are beneficial skills in secure coding. In this course, you'll explore the essential elements of Python scripting and the standard scenarios in which this language is preferable. First, you'll identify different Python scripts based on their features. Next, you'll learn how to work with variables, containers including lists, dictionaries, and tuples, conditionals, loops, and functions in a Python script. You'll learn how to carry out module imports and file reading and writing using a PowerShell script. Finally, you'll learn how to use a Python script to make a web request.
11 videos |
44m
Assessment
Badge
Building a CLI with argparse
It's common to need to deliver software that runs with a variety of options and a command line interface is a great way to let users invoke these various options. CLIs have been used to run programs since the early 1960s and are still relevant today. Their simplistic design, small footprint, and self-documentation make them ideal for automated or scheduled tasks. In this course, you'll review the history of CLIs and learn how to build a CLI using argparse, a module in the Python Standard Library. You'll examine positional and optional arguments, as well as how to use custom actions. Finally, you'll learn how to install a Python module as an editable package and explore the alternative, third-party packages for building a CLI - docopt and click. This course was originally created by Global Knowledge (GK).
9 videos |
39m
Assessment
Badge
SHOW MORE
FREE ACCESS
COURSES INCLUDED
Python Development: Getting Started with Programming in Python
Python is a beneficial language for use in a lot of development projects, particularly Java/C++ development. In this course, you'll learn the basics of Python programming. You'll start by installing Python on your local machine and practice writing code using the Python shell. Next, you'll perform basic math and logical operations in Python. You'll create Python variables and see how you can assign and access values stored in these variables. You'll then use built-in functions, which are part of the core Python programming language, to perform simple calculations and operations. Finally, you'll explore strings in Python work, creating strings using single, double, and triple quotes depending on the use case. You'll then briefly examine the use of complex data types, such as lists, tuples, sets, and dictionaries. When you're finished with this course, you'll be able to execute simple Python commands on Jupiter notebooks.
13 videos |
1h 28m
Assessment
Badge
Python Development: Performing Operations with Complex Data Types
All values in Python are classified into data types. One of these, known as complex data types, facilitates using complex numbers. In this course, you'll learn how to work with complex data types in Python. You'll start by exploring the list data type, which contains an ordered collection of elements. You'll then perform several different operations on lists, such as accessing, adding, and removing elements and implementing slicing operations. Next, you'll work with tuples and examine how tuples contain an ordered collection of elements but are immutable in nature. You'll also work with sets and dictionaries. Finally, you'll explore the nuances of the copy operation for complex data types. When you're finished with this course, you'll be able to use the right Python data type to store your data and perform basic operations using these complex data types.
14 videos |
1h 54m
Assessment
Badge
Python Development: Working with If Statements, Loops, & Comprehensions
A handy procedure in Python for controlling the execution order of program statements is to implement branching operations using conditional statements, such as 'if' and 'else'. In this course, you'll learn how to use statements, loops, and comprehensions. First, you'll implement the conditional if statement. Then you'll use the else and elif statements. Moving on, you'll use Python's looping constructs, including the for-loop to iterate over elements in complex data types as well as over lists, tuples, and dictionaries. You'll use the while-loop and the break, continue, and pass keywords to further control loop execution. Finally, you'll implement list comprehension in Python, an elegant and efficient way of generating lists using 'for loops.' When you're finished with this course, you'll be able to write conditional statements in your code and perform looping and branching operations using for and while loops.
13 videos |
1h 45m
Assessment
Badge
Python Development: Defining, Configuring, & Invoking Functions
In Python, functions are essentially first-class citizens. They are objects in Python, just like other primitive and complex data types, and have a valuable purpose. In this course, you'll learn how to define and invoke functions in Python. First, you'll define a function using the def keyword and specify input arguments and return values from functions. You'll then work with positional arguments and keyword arguments. Next, you'll define functions with default values for arguments and a variable number of arguments. Along the way, you'll also examine how arguments can be pass-by-value or pass-by-reference. Finally, you'll explore the characteristics of Python functions that make them first-class citizens. When you're finished with this course, you'll have a solid grasp of the foundations of support for functions in Python and be able to use Python functions in your development work.
13 videos |
1h 44m
Assessment
Badge
Python Development: Leveraging Functions with Lambdas, Generators, Closures, & Decorators
Lambdas are great for on-off use and, once stored in a variable, behave exactly like other function objects in Python. In this course, you'll learn how to create anonymous functions in Python using lambdas. You'll start by creating generator functions in Python to generate infinite sequences using the yield keyword. You'll then illustrate how these generator functions can be resumed from just after the previous yielded value. Moving along, you'll demonstrate how closures in Python are nested functions that keep track of local variables in the outer function. You'll also illustrate how decorators - bits of code allowing you to modify other pre-existing code in your program - can be implemented using closures. When you're finished with this course, you'll have a good grip of functions in Python, which allow you to perform some incredibly complex and powerful operations.
11 videos |
1h 31m
Assessment
Badge
Python Development: Creating Classes, Handling Errors, & Importing Modules
Python classes act like blueprints for establishing a new type of object with its own set of properties and methods. In this course, you'll learn how to define and instantiate classes in Python. You'll start by using the init() method to initialize your class's member variables and the self keyword to reference a class's current instance. You'll then illustrate the differences between the self keyword in Python and the "this" keyword in Java. Next, you'll examine how errors in Python can be handled using the try-except-finally block and how the error handling mechanism in Python is similar to Java exception handling. Finally, you'll import other Python libraries into your current Python program, using classes and functions defined in one Python file in another file using the import statement. When you're finished with this course, you'll be able to set up Python classes for various uses in your development projects.
9 videos |
1h 16m
Assessment
Badge
SHOW MORE
FREE ACCESS
COURSES INCLUDED
Introduction to Using PyCharm IDE
PyCharm is one of the most intuitive and feature-rich integrated development environments (IDEs) available for Python development. Explore some of the important features of this IDE, such as debugging with breakpoints, Python package installation, and customizing syntax highlighting, in this 11-video course. Key concepts covered here include how to install and configure the PyCharm IDE on your system; how to customize syntax highlighting for various source files in Python project and how to minimize typing errors by using the auto-complete feature. Next, learn to apply name changes to variables and functions to all their references; learn the state of an application in the middle of code execution with the use of breakpoints; and use the step into feature to get inside function calls and step over to run them in one go. Finally, learn to pause code execution at a line only under a specified condition; and learn to use the resume button to ensure that code execution only pauses at breakpoints.
11 videos |
1h 16m
Assessment
Badge
COURSES INCLUDED
Flask in Python: An Introduction to Web Frameworks & Flask
Explore the steps involved in a web request and the role of web applications in this web development process in this 8-video course examining various pieces that can make up a web application, and the role of the web framework in defining it. Begin by observing a widely used framework, often defined as a microframework, written in the Python language, which is Flask. You will then explore the features of the Flask framework that are available either out of the box or via extensions. Following on from this, you will delve into the roles of routes in a Flask application and the options available when defining a route function. You will learn how to recognize the need for templates when defining a web site and describe the use of jinja for this purpose. The final tutorial in this course focuses on some of the commonly used extensions in the Flask applications and recalls the purposes they serve.
8 videos |
49m
Assessment
Badge
Flask in Python: Building a Simple Web Site Using Flask
You will begin this 12-video course by learning how to install Flask-a widely used web framework written in Python language-in a virtual environment on your development machine, and then write the code for a simple "Hello World" website by using Flask. You will explore how route definitions can be altered and the benefits of running your Flask app in debug mode. Next, define a route that renders an HTML page when a URL is accessed; download and use some boilerplate HTML files so your website definition need not begin from scratch, and modify the boilerplate cascading style sheet (CSS) and HTML definitions to customize the look of a website. Learn how to generate URLs dynamically by using the url_for function; create a base Jinja template that can be inherited by other templates, along with placeholders that can be overridden; and explore how to inherit the elements from a base Jinja template in a child template HTML file. Finally, learn how to define multiple routes to point to the same route function.
12 videos |
1h
Assessment
Badge
COURSES INCLUDED
Building Web Apps Using Django: Introduction to Web Frameworks & Django
This 9-video course explores the concept of web frameworks and how they can speed up development of web applications, and examines the Django framework, a widely used framework written in the Python language. Learners begin by studying fundamentals of web requests, the steps and software required when processing web requests for static and dynamic websites. This leads into examining tasks involved in building a website and how web frameworks can speed up the process. Next, you will look at the Django framework and its features that can help to simplify web development, and the components of a Django application that are involved in processing web requests. Continue by observing what templates are in the context of Django and their use cases, and comparing Django models to database tables; then look at the role of the Django object-relational mapping layer (ORM) in mapping the two. Conclude the course by examining some of the built-in Django apps that developers can integrate into their own projects.
9 videos |
55m
Assessment
Badge
Building Web Apps Using Django: Building a Basic Website
Explore fundamentals of Django applications, from installation and the structure of a project, to implementations such as views, URLs, and templates, in this 12-video course. Begin by learning how to create a virtual Python environment and install Django, then how to generate a new Django project and describe various files that are created. You will discover how to start the built-in Django development server on the default port, as well as a specified port; define a view and URL pattern in Django to render the text "Hello World" in a web page; and generate a new app within a Django project. Learn about migrations in Django and using the manage.py script of a Django project to propagate model definitions to the database. Then observe working with Django URLs by configuring project and app-level URLs in Django; defining a view that renders an HTML file in its response; and downloading and using boilerplate HTML, CSS, and Javascript files in a Django project. Conclude by learning how to modify boilerplate HTML files to suit Django project requirements.
12 videos |
1h 18m
Assessment
Badge
Building Web Apps Using Django: Templates & User Administration
In this 11-video course, learners explore how to use templates to standardize components of a Django website, and different ways templates can be configured. Django is a widely used framework written in the Python language. Begin by learning how to add a new page to a Django website and use the Django template language to generate a URL for a URL pattern. Then move into creating a base template containing common elements for multiple pages in a Django website, and extending the base template and common elements defined within it while building individual pages in that Django website. Next, discover how to convey data from a view to a Django template in a dictionary, and apply styles defined in your CSS files to Django templates. Then move on to the Django admin interface, creating a superuser for your Django project and signing in to the Django user administration app, and using the Django admin interface to create new users. Finally, explore effects of assigning staff user status and specific permissions to Django app users.
11 videos |
1h 14m
Assessment
Badge
Building Web Apps Using Django: Models & User Registration
Django is a widely used web framework written in Python language. Explore the use of models to represent entities in a Django project, how they fit in with the project database, and how to implement user registration for a website by using various built-in Django tools in this 12-video course. Learners begin with Django models and defining entities in Django applications in model form, then learn how to propagate model definitions to a project's database by generating and running a migration script; create instances of a Django model and access model attributes; and view, update, and create instances of a Django model from the built-in admin interface. Next, explore user registration and create a view that uses Django's built-in user registration form; define the URL and template file for user registration pages for Django applications; convey notifications to website users with flash messages; and save data submitted in a user registration form by extending its definition. Conclude by learning how to install and use the Django-crispy-forms library to format a Django application's user registration page.
12 videos |
1h 23m
Assessment
Badge
Building Web Apps Using Django: Implementing Login & Logout
In this 10-video course, learners explore uses of Django's built-in login and logout views, and how to configure them. Django is a widely-used web framework using the Python language. Discover how to define a user profile, including how to define the model, set the image direction, and display profile information. Begin by building a user login page in a website with built-in Django objects, and then configure where a user is redirected to on a Django website upon successful login. Learn how to define logout template to serve as logout pages for a Django website; present different views for users who are signed into your Django website as opposed to regular users; and configure views in a Django application to render only when the user is signed in. Explore user profiles and defining the model for the profile of a user of a Django application; setting the location in a Django project directory where media can be stored; and displaying a user's information, including associated images, in a profile page.
10 videos |
1h 11m
Assessment
Badge
Building Web Apps Using Django: Generic Views
Explore various Django class-based generic views, which help to simplify the tasks of viewing, creating, editing, and deleting instances of Django models, in this 14-video course. Django is a widely used web framework written in the Python language. You will begin with a two-part tutorial on updating forms in a Django app: part 1 on defining forms and a view function, and part 2 on configuring update forms. Then explore how to use the built-in generic views: ListView to list instances of a model in your Django project; DetailView; CreateView; UpdateView, and also DeleteView. Discover how to configure permissions for the DeleteView; generate an archive of your Django model instances using the ArchiveIndexView; and create an archive of Django model instances, categorized by year, using the YearArchiveView. A two-part tutorial on applying finishing touches concludes the course: part 1 on defining an "About Us" page for your Django application, and part 2 on setting a customized 404 error page for your Django website.
14 videos |
1h 44m
Assessment
Badge
SHOW MORE
FREE ACCESS
COURSES INCLUDED
Machine Learning & Data Analytics
Explore critical machine learning (ML) and deep learning concepts and the various categorizations of algorithms and their implementations using Python.
10 videos |
1h 3m
Assessment
Badge
Supervised, Unsupervised & Deep Learning
Discover how to implement various supervised and unsupervised algorithms of machine learning using Python, with the primary focus of clustering and classification.
10 videos |
1h 30m
Assessment
Badge
Deep Learning & Neural Network Implementation
Discover how to implement neural network with data sampling and workflow models using scikit-learn, and explore the pre and post model approaches of implementing machine learning workflows.
10 videos |
1h 2m
Assessment
Badge
Implementing ML Algorithm Using scikit-learn
Discover how to implement data classification using various techniques, including Bayesian, and learn to apply various search implementations with Python and scikit-learn.
10 videos |
1h 13m
Assessment
Badge
Implementing Robotic Process Automation
Discover how to implement Robotic Process Automation (RPA) using Python, and explore various RPA frameworks with the practical implementation of UiPath.
10 videos |
1h 2m
Assessment
Badge
SHOW MORE
FREE ACCESS
COURSES INCLUDED
Data Processing
Working with databases, regular expressions, and XML data are common tasks for DevOps in Python. Explore how to perform these common tasks.
9 videos |
48m
Assessment
Badge
Applications
Explore web programming and GUI programming in Python.
12 videos |
1h 2m
Assessment
Badge
Python - Introduction to NumPy for Multi-dimensional Data
ThisSkillsoft Aspire course explores NumPy, a Python library used in data science and big data. NumPy provides a framework to express data in the form of arrays, and is the fundamental building block for several other Python libraries. For this course, you will need to know basics of programming in Python3, and should also have some familiarity in working with Jupyter notebooks. You will learn how to create NumPy arrays and perform basic mathematical operations on them. Next you will see how to modify, index, slice, and reshape the arrays; and examine the NumPy library's universal array functions that operate on an element-by-element basis. Conclude by learning how to iterate various options through NumPy arrays.
11 videos |
58m
Assessment
Badge
Python - Advanced Operations with NumPy Arrays
NumPy is oneof the fundamental packages for scientific computing that allows data to be represented in dimensional arrays. This course covers the array operations you can undertake such as image manipulation, fancy indexing, and broadcasting. To take this Skillsoft Aspire course, you should be comfortable with how to create, index, and slice Numpy arrays, and apply aggregate and universal functions. Among the topics, you will learn about the several options available in NumPy to split arrays. You will learn how to use NumPy to work with digital images, which are multidimensional arrays. Next, you will observe how to manipulate a color image, perform slicing operations to view sections of the image, and use a SciPy package for image manipulation. You will learn how to use masks, an array of index values, to access multiple elements of an array simultaneously, referred to as Sansi indexing. Finally, this course covers broadcasting to perform operations between mismatched arrays.
13 videos |
1h 7m
Assessment
Badge
Python Unit Testing: An Introduction to Python's unittest Framework
This 8-video course explores the unit-test framework in Python. To take this course, you should have experience in Python programming and the use of the Linux shell. The unit-test framework (also known as PyUnit) is modeled on JUnit and simplifies the automation of tests for Python applications. You will learn to use the unit-test framework to define tests for your application source code to ensure that it behaves in a specified manner. In this course, learners will write a sample test, and then expand the test scripts to include multiple tests. You will learn how to sequence the execution of tests in scripts, and how to filter out tests which do not require a specific run. Next, you will learn how to pass the output of test executions to identify the results of your tests, and how to diagnose test failures. You will learn how to run specific tests from among multiple tests in your scripts. Finally, this course demonstrates how to skip the execution of tests by using the skip decorator.
8 videos |
50m
Assessment
Badge