Module 1: Preparatory Session - Linux and Python
- Python
- Linux
Module 2: Data Analysis With MS-Excel
- Excel Fundamentals
- Excel For Data Analytics
- Data Visualization with Excel
- Excel Power Tools
- Classification Problems using Excel
- Information Measure in Excel
- Regression Problems Using Excel
Module 3: Data Wrangling with SQL
- SQL Basics
- Advanced SQL
- Deep Dive into User Defined Functions
- SQL Optimization and Performance
Module 4: Python with Data Science
- Extract Transform Load
- Data Handling with NumPy
- Data Manipulation Using Pandas
- Data Preprocessing
- Data Visualization
Module 5: Linear Algebra and Advanced Statistics
- Descriptive Statistics
- Probability
- Inferential Statistics
Module 6: Machine Learning
- Introduction to Machine Learning
- Regression
- Classification
- Clustering
- Supervised Learning
- Unsupervised Learning
- Performance Metrics
Module 7: Deep Learning Using TensorFlow
- Artificial Intelligence Basics
- Neural Networks
- Deep Learning
Module 8: Power BI
- Power BI Basics
- DAX
- Data Visualization with Analytics
Module 9: Deploying Machine Learning Models with Cloud
- Deploying Machine Learning Models with Cloud
- Deploying Machine Learning Models
Module 10: Git
- Version Control
- GIT
Module 11: Data Science Capstone Project
Module 12: Business Case Studies
- Recommendation Engine
- Rating Predictions
- Census
- Housing
- Object Detection
- Stock Market Analysis
- Banking Problem
Module 13: Natural Language Processing
- Text Mining, Cleaning, and Pre-processing
- Text classification, NLTK, sentiment analysis, etc.
- Sentence Structure, Sequence Tagging, Sequence Tasks, and Language Modeling
- AI Chatbots and Recommendations Engine
Module 14: Computer Vision
- RBM and DBNs & Variational Autoencoder
- Object Detection using Convolutional Neural Net
- Generating images with Neural Style and Working with Deep Generative Models
- Distributed & Parallel Computing for Deep Learning Models
- Reinforcement Learning
- Deploying Deep Learning Models and Beyond
Module 15: Data Science at Scale with Pyspark
- Big Data and Spark
- RDDs
- Advanced Concepts & Spark-Hive
Module 16: Machine Learning Certification Exam Prep
- Explain Machine Learning Certification Options
- Discuss 50+ Important Machine Learning Certification Questions
- Practice Machine Learning Certification questions
Module 17: Resume Preparation, Interview and Job Assistance
- Prepare Crisp Resume as Machine Learning Developer
- Discuss common interview questions in Machine Learning
- Explain students what jobs they should target and how