Sessions

- DATA ANALYSIS FOUNDATION
1. DATA ANALYSIS FOUNDATION
2. CLASSIFICATION OF ANALYTICS
3. CRIP-DM ModelS
4. UNIVARIATE DATA ANALYSIS
5. DATA ANALYSIS WITH VISUAL CHARTS
6. BI-VARIATE
- : PYTHON FOUNDATION
1. PYTHON BASICS
2. PYTHON CONTROL STATEMENTS
3. PYTHON DATA STRUCTURES
4. PYTHON FUNCTIONS
5. PYTHON NUMPY
- VERSION CONTROL WITH GIT
1. DATA SCIENCE ESSENTIALS
2. DATA ENGINEERING FOUNDATION
3. PYTHON FOR DATA ANALYSIS
4. VISUALIZATION WITH PYTHON
5. STATISTICS
6. MACHINE LEARNING INTRODUCTION
- BUSSINESS INTELLIGENCE
1. Power Bi
2. Tableau
3. Excel
4. Quikview
- DATA ANALYSIS ASSOCIATE
1. COMPARISION AND CORRELATION ANALYSIS
2. VARIANCE AND FREQUENCY ANALYSIS
3. RANKING ANALYSIS
4. BREAK EVEN ANALYSIS
5. Time Series and Trend Analysis
6. DATA ANALYSIS BUSINESS REPORTING
- ADVANCED DATA ANALYTICS
1. DATA ANALYTICS FOUNDATION
2. OPTIMIZATION MODELS
3. PREDICTIVE ANALYTICS WITH REGRESSION
4. DECISION MODELING
- PREDICTIVE ANALYTICS WITH ML
1. MACHINE LEARNING INTRODUCTION
2. ML ALGO: LINEAR REGRESSSION
3. ML ALGO: LOGISTIC REGRESSION
4. ML ALGO: KNN
5. ML ALGO: K MEANS CLUSTERING
6. ML ALGO: DECISION TREE
7. ML ALGO: SUPPORT VECTOR MACHINE (SVM)
8. ARTIFICIAL NEURAL NETWORK (ANN)
9. PROJECT: PREDICTIVE ANALYTICS WITH ML
- DATABASE : SQL AND NoSQL
1. DATABASE INTRODUCTION
2. SQL BASICS
3. DATA TYPES AND CONSTRAINTS
4. DATABASES AND TABLES (MySQL)
5. SQL JOINS
6. SQL COMMANDS AND CLAUSES
7. DOCUMENT DB/NO-SQL DB