Aspire Journeys

Data Scientist: Machine Learning

  • 30 Courses | 12h 5m
  • 42 Labs | 41h 55m
Machine Learning Data Scientists use data to build models and generate meaning from data.

This no-code course introduces the foundational how’s and why’s of data. How do statistics help us make conclusions from data? Why is good design critical for communicating data stories through data viz? What are the different kinds of analysis we can perform on a dataset? This course will help you feel empowered to answer these questions (and more!) and work with data with confidence. You will learn how to evaluate data quality, interpret statistical conclusions, create and read data visualizations, and analyze data responsibly.

  • 5 Courses | 4h 25m
  • 2 Labs | 2h

We live in a data-driven world: people search through data to find insights to inform strategy, marketing, operations, and a plethora of other categories. There are a ton of businesses that use large, relational databases, which makes a basic understanding of SQL a great employable skill not only for data scientists, but for almost everyone. In this course, you'll learn how to communicate with relational databases through SQL. You'll learn—and practice with 4 projects—how to manipulate data and build queries that communicate with more than one table.

  • 1 Course | 20m
  • 5 Labs | 5h

In this course, you will learn about exploratory data analysis techniques in Python, including: - EDA for data preparation - Summary statistics - Data visualization techniques - EDA prior to building a machine learning model Prior to taking this course, you should have some knowledge of base Python and experience with pandas DataFrames. Exploratory data analysis is an important part of any Data Scientist or Analyst's workflow, so we highly recommend this course for anyone who is interested in working with data.

  • 2 Courses | 20m
  • 4 Labs | 4h


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