Aspire Journeys
Python Novice to Pythonista
- 52 Courses | 62h 4m 39s
- 4 Labs
- Includes Test Prep
Python continues to be one of the fastest growing programming languages in the market today. Because of its ease of use and numerous supporting frameworks, it’s widely used in web development, writing scripts, automating tasks, data science and even cybersecurity. In this Skillsoft Aspire Journey you will explore the different stages required to become a Pythonista.
Track 1: Python Novice
In this track of the Pythonista Skillsoft Aspire Journey, the focus is getting started with Python, complex data types, conditional statements and loops, and first class functions and lamdas.
- 12 Courses | 14h 50m 29s
- 1 Lab
Track 2: Python Apprentice
In this track of the Pythonista Skillsoft Aspire Journey, the focus is Python classes and inheritance and also data structures and algorithms.
- 15 Courses | 17h 19m 3s
- 1 Lab
Track 3: Python Journeyman
In this track of the Pythonista Skillsoft Aspire journey, the focus will be on Python Unit Testing, Python HTTP requests, Flask in Python, and Python concurrent programming.
- 14 Courses | 16h 10m 39s
- 1 Lab
Track 4: Pythonista
In this track of the Pythonista Skillsoft Aspire Journey, the focus is unit testing, developing and debugging using the PyCharm IDE, wrangling Excel data, network programing, and hashing and encryption algorithms.
- 11 Courses | 13h 44m 28s
- 1 Lab
COURSES INCLUDED
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
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
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 |
56m
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 |
48m
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
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
Assessment
Badge
