Coding will be on R & Python

Module 1 : Basic of R & Python Duration : 10 Hrs

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

Module 1 : 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 2 : Adv. Statistics Duration : 10 Hrs

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

Module 3 : 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 4: 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 5: 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 6: Project Work

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