| S. No. | Topic | No. of Hours |
|---|---|---|
| Topic 01 |
Python (Internals, do’s and don’ts) Architecture, Data StructureSub-Topic Installation of Anaconda Prompt Jupyter Notebook-An Overview Shorcut Lkeys in Jupyter Notebook Data Types in Python Rules for Naming the Variables List Tuple Set Dictionary |
4 |
| Topic02 |
Data Analysis , Manipulation with numpy and pandas Python data science package to manipulate, calculate and analyze dataSub-Topic Machine Learning Libraries Numpy-Hands on Pandas-Hands on |
3 |
| Topic 03 |
Exploratory Data Visualization in Python with matplotlib Learn how to explore, visualize, and extract insights from dataSub-Topic Data Visualization Matplotlib-Hands on Seaborn-Hands on |
4 |
| Topic04 |
Statistical Thinking in Python (Part 1) Build the foundation you need to think statistically and to speak the language of your dataSub-Topic Measures of Central Tendency Measures of Dispersion IQR Statistics-Hands-On |
4 |
| Day 05 |
Supervised Learning and UnSupervised Learning Classification, Regression, Fine-tuning your modelSub-Topic Supervised Learning Unsupervised Learning Linear Regression Metrics in Linear Regression Hands-on in Linear Regression |
3 |
| Topic 06 |
Logistic regressionSub-Topic Logistic Regression Metrics in Logistic Regression Hands-on in Logistic Regression |
1 |
| Topic 07 |
SVM, Linear RegressionSub-Topic Support Vector Machine Hands on in SVM |
2 |
| Topic 08 |
Preprocessing for Machine Learning in Python Introduction to Data Preprocessing, Standardizing DataSub-Topic Exploratory Data Analysis Missing Values Outliers Standardization Mnormalization Feature Scaling and Selection |
3 |
| Topic 09 |
Tree Based Models Classification and Regression TreesSub-Topic Decision Tree Bagging Boosting Random Forest |
4 |
