Introduction to Data Science
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5 sessions
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About
Have a background in statistics or took AP Statistics? Ever interested in computer science?
This course is for you. We will study probability and inference with an emphasis on computing. We will explore the use of Python, SciPy, Numpy and Pandas, and write a few packages. If enough demand, we will also explore Pytorch and/or Tensorflow.
By the end of this course, you should:
- Be able to use Python and statistics packages to run tests for data validation and/or probability
- Gain insight on how statistical packages are written.
Tutored by
✋ ATTENDANCE POLICY
While attendance is not mandatory, we highly recommend to attend every lecture, especially for those with weaker backgrounds in computer science and statistics.
SESSION 1
17
Feb
SESSION 1
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Mon 12:30 AM - 1:15 AM UTCFeb 17, 12:30 AM - 1:15 AM UTC
Introduction to Data Science. The following is our topics:
- Brief intro to data science, what it is about, what you'll need, etc.
- Environment Setup
- Beginner intro to Python
SESSION 2
21
Feb
SESSION 2
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Fri 12:30 AM - 1:15 AM UTCFeb 21, 12:30 AM - 1:15 AM UTC
Elementary Statistics in Python
- Lists with Numpy
- Basic use of Numpy (Averages, Medians, Modes)
- Matplotlib (Graphing, labels, titles)
SESSION 3
28
Feb
SESSION 3
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Fri 12:30 AM - 1:15 AM UTCFeb 28, 12:30 AM - 1:15 AM UTC
Probability in Python:
- Randomization in Python
- Probability Analysis
- Print statement in Python
SESSION 4
7
Mar
SESSION 4
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Fri 12:30 AM - 1:15 AM UTCMar 7, 12:30 AM - 1:15 AM UTC
Inference 1: t tests
- T-test in Scipy
- Writing of T-test in Scipy
- 2-Sample t test in Scipy
- Writing of 2-sample t test in Scipy
SESSION 5
13
Mar
SESSION 5
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Thu 11:30 PM - Fri, 12:15 AM UTCMar 13, 11:30 PM - Mar 14, 12:15 AM UTC
Inference 2: z tests
- Z-test in Scipy
- Writing of Z-test in Scipy
- 2-Sample Z test in Scipy
- Writing of 2-sample Z test in Scipy