What will you be able

After taking this course you will be able to use SQL to manage databases like a data scientist on the job. You will also use Python for statistical analysis and create compelling data visualizations to show you findings. Finally, you will create artificially intelligent models that can automate data processes, recognize patterns, and make recommendations.

Recommended duration: 3 months (24 hours) 
If you have any questions or concerns, feel free to reach out to us at [email protected]

What will you

The Importance of Data and SQL Syntax
Learn about the methods data analysts use to find relevant information in datasets as well as the basic syntax of the SQL language.

SQL: Basic

Learn the basics of SQL databases and write your first queries.

SQL: Intermediate

Increase your SQL knowledge by learning about aggregates and multiple tables.

Get Personal with SQL

Set up a SQL database on your own computer and practice what you’ve learned so far.

Analyze Real Data with SQL

Use what you’ve learned so far to solve real-world problems.

Python Functions and Logic

Learn the basics of abstraction. Build repeatable blocks of code and instruct your program how to execute the instructions you provide.

Python Lists and Loops

Learn about Python lists for organizing your data and loops for repeating blocks of code.

Advanced Python

Learn how to code with Python more efficiently using list comprehensions and lambda functions.

Python Cumulative Project

Learn about how to fit a line to some points while combining all of your knowledge of Python so far.

Data Analysis with Pandas

Learn how to use Pandas, the go-to Python library with tools for data manipulation and analysis.

Data Visualization

Using Python, learn how to present data in an interesting way that compels others to care about your findings.

Visualization Cumulative Projects

Practice your data visualization skills in real-world situations.

Data Visualization Capstone Project

Complete a project that will test all of your data visualization skills.

Learn Statistics With Python

Learn how to calculate and interpret several descriptive statistics.

Introduction to Statistics with NumPy

Learn how this Python library is used to store arrays of numbers, organize large amounts of data, and perform statistical calculations.

Hypothesis Testing with SciPy

Learn the Python module for comparative statistics in order to perform code tests.

Practical Data Cleaning

Pull and clean data from the web with this Python based course.

Data Analysis Capstone Project

Complete two capstone projects that will test all of your data analysis skills.

Learn Web Scraping with Beautiful Soup

Learn Beautiful Soup, a popular Python library for web scraping.

Machine Learning: Supervised Learning 

Discover how algorithms learn from examples of past outcomes.

Supervised Machine Learning Cumulative Project

During this project you’ll use your understanding of supervised machine learning models to analyze data.

Machine Learning: Unsupervised Learning 

Learn about how to perform learning on a dataset with nothing to base it off of.

Unsupervised Machine Learning

Create a project on that shows your understanding of unsupervised machine learning.

Perceptrons and Neural Networks

Learn the building blocks of neural networks and begin to create your own.

Natural Language Processing

Build the code that can power tools from virtual assistants to autocorrect.