Python for Data Science (Weekends)
| Date: | 14-Oct-17 to 18-Nov-17 |
| Location: | Practical Programming / United States |
| Category: | Education |
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.
Discover best practices for data analysis and start on the path to becoming a data scientist
Get comfortable using Python to build statistical and analytical models
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
Explore graphical techniques to see what your data looks like
Implement the core Data Science techniques of Linear Algebra, Probability, Gradient Descent, and Linear Regression
Build your own analytical tools with Python from scratch
Become familiar with industry standards and learn the best practices for writing code
By the end of this course, you will have a Data Analytics Project to present to potential employers.
Who is this program for:
Novice and people with no previous programming experience, seeking a comprehensive course to enter the field of data and analytics and become data scientists.
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.
Why Python:
Many other programming solutions can be used for Data Science, however we chose high-level programming language Python because it is easy to learn if you are new to programming and it is in high demand.
Discover best practices for data analysis and start on the path to becoming a data scientist
Get comfortable using Python to build statistical and analytical models
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
Explore graphical techniques to see what your data looks like
Implement the core Data Science techniques of Linear Algebra, Probability, Gradient Descent, and Linear Regression
Build your own analytical tools with Python from scratch
Become familiar with industry standards and learn the best practices for writing code
By the end of this course, you will have a Data Analytics Project to present to potential employers.
Who is this program for:
Novice and people with no previous programming experience, seeking a comprehensive course to enter the field of data and analytics and become data scientists.
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.
Why Python:
Many other programming solutions can be used for Data Science, however we chose high-level programming language Python because it is easy to learn if you are new to programming and it is in high demand.
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