Machine Learning with Python

This course will cover the in-depth study and implementation of following topics:

Machine Learning Foundations:

1. Mathematics and Science behind Machine Learning
2. Functions and Graphs
3. Statistics and its Applications
4. Introduction to Probability Theory

Machine Learning:

1. Getting Started with Machine Learning

• What is Machine Learning – Examples and Applications
• Numpy and Pandas Tutorial
• Scikit Learn Tutorial
• Introduction to Model Evaluation and Validation
• Training and Testing
• Metrics for Evaluation
• 2 Mini-Projects to understand and implement Machine Learning Basics

2. Supervised Learning 

• Introduction to Supervised Learning
• Linear Regression
• Logistic Regression
• Decision Trees
• Random Forests
• Naïve Bayes Classifier
• Bayesian Statistics and Inference
• K-Nearest Neighbour
• Introduction to Neural Networks
• Introduction to Natural language Processing
• Mini Project to apply Supervised Learning Algorithms

3. Unsupervised Learning 

• Introduction to Unsupervised Learning
• K-Means Clustering
• Hierarchal Clustering
• Clustering using DBSCAN
• Clustering Mini-Project
• Feature Selection
• Principal Components Analysis (PCA)
• Feature Transformations

4. Reinforcement Learning 

• Introduction to Reinforcement Learning
• Markov decision Processes
• Game Theory Fundamentals
• Mini Project to implement Reinforcement Learning

5. Deep Learning 

• Introduction to Deep Learning
• Deep Learning tools
• TensorFlow
• Deep Neural networks
• Convolutional Neural Networks
• Neural network Mini-Project

6. Introduction to Kaggle Platform and other Data Science Competitions
7. Special Session on Creation of Data Science Portfolio – CV, LinkedIn and GitHub
8. Interview Preparation for Data Science/Machine Learning

9. Machine Learning Industry Project: This will be a industry-specific project to solve a real-world problem using different Machine Learning techniques learned in the overall course.

Instructor profile: Gaurav Goel has done MS from BITS, Pilani and has around 13 years of experience in all phases of design, development, implementation and management of Data Analytics and BI/Data warehousing across pharmaceutical, healthcare, manufacturing, and banking industries. Currently he is heading the Data Science Practice in a Healthcare startup, building data-driven products for Pharma Industry. Previously he has worked with Oracle and Royal Bank of Scotland. He is passionate about technology especially Artificial Intelligence and seeks to share knowledge with people who share the common passion.

Duration: 3 Months (72 hours)

Schedule: Weekends (Sat, Sun) 3 hours per session

Contact: +91 9871338064

Enrollment link: http://itbodhi.com/courses/MachineLearning.html