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PYTHON_ML_DS

Module 1 - Python Programming

  1. Intro to Python
  2. Data Structures in Python (List, Tuple, Set, Dictionary)
  3. Control Statements (Decision and Loops)
  4. Functions and Modules

Module 2 - Python for Data Science

  1. Numpy
  2. Pandas
  3. Missing Value Treatment
  4. Exploratory Data Analysis (Matplotlib, Seaborn and Plotly)

Module 3 - Machine Learning

  1. K - Nearest Neighbours
  2. Linear Regression
  3. Logistic Regression
  4. Gradient Descent
  5. Decision Trees
  6. Support Vector Machines
  7. K - Means
  8. Principal component Analysis

Module 4 - Case Studies

Module 5 - Deep Learning

Internship Tasks

  • Task - 1 -> Make a Web Portfolio

    • Use HTML and Bootstrap for frontend.
    • Use Flask for backend.
  • Task - 2 -> AMCAT Data Analysis

    • Data Set Click Here
    • Data Set Description Click Here
    • Task Description - Analyse the data using pandas and come up with 5 observations.
    • P.S - Use whatever we have already covered in the class. Also look into more pandas topic like pivot tables and cross tab for analysis.

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