Python Data Science Classes Chicago, IL

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

In this course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

Learn the essential skills and tools to become a Python Developer. This beginner-friendly course teaches students Python for software development with Django and Django REST in addition to other developer tools such as Git and SQL. After completing this certificate, students will be able to apply for the following roles: Python Developer, Back End Developer, Software Engineer, and many more.

Step into the world of data with the University of Illinois Chicago's Data Analytics Bootcamp. In this 10-26 week online program, you'll master the art of data analysis using tools like Excel, SQL, and Python and work towards industry certifications, setting a solid foundation for a career as a Data Analyst or Insights Analyst.

This 1-week data analytics course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

This 18-hour Machine Learning & Automation for Finance course teaches advanced skills in machine learning in Python. Students in this course will develop advanced skills in the Python language, learn how to use object-oriented programming and regression models, and apply these concepts to a real world problem. They will also learn how to use Python to build predictive financial models and to create budgets that may be exported.

This course on data wrangling with Python offers a 3-day comprehensive introduction. The purpose of this course is to give an immersive foundation that equips students with the most critical data analysis tools. Students will learn how to work with NumPy, Pandas, and MatPlotLib to calculate descriptive statistics, work with alternative data sources, and scrape web pages. The course culminates with a real-life data wrangling project.

In this Python automation course, students will learn to automate tasks using Python for various applications. This course is meant for those with prior Python experience looking to learn automation techniques like scheduling programs, updating spreadsheets, and web scraping. Topics include HTML and CSS basics, web scraping techniques, working with spreadsheets using Python, and scheduling scripts. This course offers flexible scheduling options plus a free retake for students to refresh the material.

This data science with Python course is for people with a basic knowledge of programming with Python. This comprehensive course will explain how to work with some of the most widely-used data analysis and visualization modules, such as Pandas, matplotlib, Numpy, Scipy, and more. The course will begin with a review of the basic syntax and data structures of Python before moving on to object-oriented programming, scientific computation, and data visualization. The final unit will teach you how to manipulate data with Pandas before you complete a final project.