Python for Data Science

Chicago, 29 E Madison St.
Python for Data Science
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  • Art
    Instructor
  • Python
    Categories
  • Data Science
    Categories
  • Beginner
    Skill Level

ABOUT THE COURSE

Our program serves as the foundation for many well-known concepts of data science. We teach practical techniques and algorithms for extracting and studying useful knowledge from data. This course is not a theory class as we believe there are many ways to learn statistics and analytics concepts on your own. We are providing students with a set of practical tools for data science and knowledge on how to apply Python to solve linear algebra, statistics, and probability problems. This course is designed to fill the gap between theoretical academic research and the needs of the industry. We will start with a crash course on the basics of the Python programming language and then learn how to use Python to turn raw data into insight and knowledge.

WHAT TO EXPECT FROM THIS COURSE

What to expect from this program: Fundamental introduction to Data Science using Python programming language, practical application of different statistical, analytical and linear algebra models to a variety of data science projects, and feeling comfortable enough to apply acquired knowledge on your own seeking a junior data scientist position.

How this program is organized:

Lecture on new topics takes about 90 minutes and starts at 10.00am. After lecture, students start working on new exercises with instructor guidance. Around 1.00pm students present and discuss their work with instructors, learn alternative solutions, and best practices from instructors and invited data scientist professionals.

WHAT WILL YOU LEARN

  • Discover best practices for data analysis and start on the path to becoming a data scientist
  • Discover best practices for data analysis and start on the path to becoming a data scientist.
  • Learn and practice essential tools for data analytics: NumPy, Pandas and Matplotlib
  • Learn to find solutions to problems by analyzing data using appropriate tools
  • Master your analytical skills by working on real life projects
  • Implement the core Data Science techniques of Linear Algebra, Probability, Gradient Descent, and Linear Regression
  • By the end of this course, you will have a Data Analytics Project to present to potential employers

How this program is organized:

Lecture on new topics takes about 90 minutes and starts at 10.00am. After lecture, students start working on new exercises with instructor guidance. Around 1.00pm students present and discuss their work with instructors, learn alternative solutions, and best practices from instructors and invited data scientist professionals.

Things To Remember

  • Please bring your own laptop to class.
  • We will help you to install all the programs you need in class.
  • If you withdraw one day before the course start date, any deposit paid will be refunded in full.
  • If you cannot attend classes for which you were charged, you could join next cohort and make up the missed classes.