Coding will be on Python

Module 1 : Basic of Python Duration : 10 Hrs

1. Why Python?
2. Python Installation
3. Basics of Python
4. Libraries
5. Operators in Python
6. Data Types in Python
7. Importing Data in Python
8. Plots in Python
9. Descriptive Statistics

Module 2 : Basic Statistics Duration : 10 Hrs

1. Introduction to Data Science.
2. Data Types.
3. Central Tendency.
4. Probability.
5. Normal Distribution & Standardization.
6. Sampling Theory.
7. Assignments

Module 3 : Adv. Statistics Duration : 10 Hrs

1. Z-Distribution & T- Distribution.
2. Hypothesis Testing.
3. Correlation Analysis.
4. Regression Types.
5. Assignments

Module 4 : Data Mining (Supervised) Duration : 10 Hrs

1. Linear Regression.
2. Logistic Regression.
3. Decision Tree.
4. Random Forest.
5. K- Nearest Neighbor.
6. Naïve Bayes.
7. Assignments.

Module 5: Data Mining (Unsupervised) Duration: 10 Hrs

1. Hierarchical Clustering.
2. K-means Clustering.
3. Dimension Reduction.
4. Random Forest.
5. Market Basket Analysis.
6. Assignments.

Module 6: Timeseries / Forecasting Duration: 10 Hrs

1. What is Forecasting?
2. Why Forecasting?
3. Forecasting Strategies?
4. Plots.
5. Partitioning.
6. Model Building.
7. Evaluating.

Module 7: Project Work

1. One Supervised Learning Project
2. One Unsupervised Learning Project
3. Dimension Reduction and Regression Project.