Course curriculum

  • 1

    Introduction to Data Science

    • Introduction to Data Science
  • 2

    Introduction to Python

    • Introduction to Python
  • 3

    Python basic constructs

    • Python basic constructs
  • 4

    Writing OOP in Python

    • Writing OOP in Python

  • 5

    NumPy for mathematical computing

    • NumPy for mathematical computing
  • 6

    Data Analysis, Data Manipulation (Pandas)

    • Data Analysis, Data Manipulation (Pandas)
  • 7

    Data visualization with Matplotlib

    • Data visualization with Matplotlib
  • 8

    Machine Learning

    • Machine Learning
  • 9

    Supervised Learning - Regeression - Linear Regression

    • Supervised Learning - Regeression - Linear Regression
  • 10

    Supervised Learning - Classification - Logistic Regression

    • Supervised Learning - Classification - Logistic Regression
  • 11

    Supervised Learning - Classification - Decision Trees

    • Supervised Learning - Classification - Decision Trees
  • 12

    Supervised Learning - Classification - Random Forests

    • Supervised Learning - Classification - Random Forests
  • 13

    UnSupervised learning - Clustering - K Means

    • UnSupervised learning - Clustering - K Means
  • 14

    Web Scraping with Python

    • Web Scraping with Python