Postgraduate Diploma in Machine Learning and Artificial Intelligence

Curriculum

Module 1: Applied Machine Learning

Supervised Learning

  • Regression
    Maximum Likelihood, Least Squares, Regularization
  • Bayesian Methods
    Bayes Rule, MAP Inference, Active Learning
  • Foundational Classification Algorithms
    Nearest Neighbors, Perceptron, Logistic Regression
  • Refinements to Classification
    Kernel Methods, Gaussian Process
  • Intermediate Classification Algorithms
    SVM, Trees, Forests and Boosting

Unsupervised Learning

  • Clustering Methods
    K-Means Clustering, E-M, Gaussian Mixtures
  • Recommendation Systems
    Collaborative Filtering, Topic Modeling, PCA
  • Sequential Data Models
    Markov and Hidden Markov Models, Kalman Filters
  • Association Analysis
    Maximum
  • Clustering Methods - II
    Model Comparisons, Analysis Considerations
Module 2: Applied Artificial Intelligence
  • Introduction to Artificial Intelligence
  • Intelligent Agents and Uninformed Search
  • Heuristic Search
  • Adversarial Search and Games
  • Constraint Satisfaction Problems
  • Reinforcement Learning
  • Logical Agents
  • AI applications: Natural Language Processing
  • AI Applications and Course Review
Module 3: Capstone Project
PRE-REQUISITES: The course requires an undergraduate knowledge of statistics, (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation, etc.) calculus, linear algebra (vectors, matrices, derivatives), and probability.

You should be comfortable with Python or any other programming language. All assignments/application projects will be done using the Python programming language with one or more of the following packages: pandas, NumPy, Matplotlib, seaborn, scikit-learn, PyMC3, etc.


APPLICATION ASSIGNMENTS

Movie Recommendation Engine

House Price Prediction

Human Activity Recognition

Credit Card Fraud Detection

Market Segmentation

Search Algorithms

Adversarial Search and Games

Machine Learning

Constraint Satisfaction Problems

Reinforcement Learning

Natural Language Processing

 

APPLICATION DETAILS

Program fee: USD 3,000Application Fee: (Non-Refundable) USD 50 Program Starts: 28 March 2019Application Deadline: 26 March 2019

APPLICATION DETAILS

Program fee: USD 3,000
Application Fee: (Non-Refundable) USD 50 
Program Starts: 28 March 2019
Application Deadline: 26 March 2019

 

 

APPLICATION DETAILS

Program fee: USD 3,000Application Fee: (Non-Refundable) USD 50 Program Starts: 28 March 2019Application Deadline: 26 March 2019

Global Ivy Emeritus Institute of Management