Learn Data Science using Python Step by Step

/ RP

Here is how you can learn Data Science using Python step by step. Please feel free to reach out to me on my personal email id rpdatascience@gmail.com if you have any question or comments related to any topics.

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  1. Setup Python environment
  2. How to start jupyter notebook
  3. Open Jupyter Notebook in Browser of your Choice
  4. Install and check Packages
  5. Arithmetic operations
  6. Comparison or logical operations
  7. Assignment and augmented assignment in Python
  8. Variables naming conventions
  9. Types of variables in Python and typecasting
  10. Python Functions
  11. Exception handling in Python
  12. String manipulation and indexing
  13. Conditional and loops in Python
  14. Python data structure and containers
  15. Introduction to Python Numpy
  16. Introduction to Python SciPy
  17. Introduction to Python Pandas
  18. Python pivot tables
  19. Pandas join tables
  20. Missing value treatment
  21. Dummy coding of categorical variables 
  22. Basic statistics and visualization
  23. Data standardization or normalization
  24. Linear Regression with scikit- learn (Machine Learning library)
  25. Lasso, Ridge and Elasticnet Regularization in GLM
  26. Logistic Regression with scikit- learn (Machine Learning library)
  27. Hierarchical clustering with Python
  28. K-means clustering with Scikit Python
  29. Decision trees using Scikit Python
  30. Regression Decision Trees with Scikit Python
  31. Support Vector Machine using Scikit Python
  32. Principal Component Analysis (PCA) using Scikit Python- Dimension Reduction
  33. Linear Discriminant Analysis (LDA) using Scikit Python- Dimension Reduction and Classification
  34. Market Basket Analysis or Association Rules or Affinity Analysis or Apriori Algorithm
  35. Recommendation Engines using Scikit-Surprise
  36. Price Elasticity of Demand using Log-Log Ordinary Least Square (OLS) Model
  37. Timeseries Forecasting using Facebook Prophet Package
  38. Model Persistence and Productionalization Using Python Pickle
  39. Deep Learning- Introduction to deep learning and environment setup
  40. Deep Learning- Multilayer perceptron (MLP) in Python
  41. Deep Learning- Convolution Neural Network (CNN) in Python
  42. Other topics (coming soon)

Cheers!

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