PadhAI - Foundations of Data Science

https://padhai.onefourthlabs.in/courses/data-science​

Total Size - 16.98 GB​

Is this the right data science course for me?​

If you are familiar with programming (in any language) and comfortable with mathematics at 12th standard (high school) level, then you should be able to follow along with this course. This course is well suited for the following learning objectives:

• Understand the value of data science and the process behind using it.
• Learn the fundamentals of statistics and probability required for data science.
• Use Python to gather, store, clean, analyse, and visualise data-sets.
• Apply statistical methods to formulate and test data hypotheses
• Apply statistical inference to uncover relationships within data-sets
• Understand the role of ML and DL in the data science pipeline
• Understand real-world challenges with several case studies

Your instructors​

Mitesh Khapra and Pratyush Kumar

Mitesh and Pratyush are Assistant Professors at the Department of Computer Science and Engineering at IIT Madras. They have both industry and academic experience in working with deep learning and related areas. They are both passionate about teaching and contributing to nation building.

Data Science Course curriculum​

• 1
  

  Instructions for this course​

• 2
  

  Week 1: Introduction​

• 3
  

  Week 2 - Part 1: Engineering Data Science Systems​

• 4
  

  Week 2 - Part 2 : What is Statistics?​

• 5
  

  Week 3: Getting started with Python​

• 6
  

  Blog Contest - 1​

• 7
  

  Week 4: Descriptive Statistics (Part 1)​

• 8
  

  Week 5: Python (continued)​

• 9
  

  Week 6: Descriptive Statistics (Part 2)​

• 10
  

  Week 7: Descriptive Statistics (Part 3)​

• 11
  

  Week 8: Numpy​

• 12
  

  Week 9: Pandas​

• 13
  

  Week 10: Pandas (continued)​

• 14
  

  Week 11: Visualisation​

• 15
  

  Week 12: Visualisation (Continued)​

• 16
  

  Week 13: Approaching Open ended DS problems​

• 17
  

  Week 14: Counting​

• 18
  

  Week 15: Sample spaces & Events​

• 19
  

  Week 16: Random Variables​

• 20
  

  Week 17: Distributions & Sampling Strategies​

• 21
  

  Week 18: Distributions of Sample Statistics​

• 22
  

  Week 19: Central Limit Theorem​

• 23
  

  Week 20: Chi Square Distribution​

• 24
  

  Week 21 : Point and Interval Estimators​

• 25
  

  Week 22: Hypothesis Testing​