Indian Institute of Technology Delhi (IITD)

Certificate Programme in Machine Learning and Deep Learning (Batch-02)

The curriculum is tailored to offer participants a thorough grasp of the driving forces, fundamental concepts, techniques, and practical uses of these technologies. It encompasses fundamental Python programming, an introductory exploration of data analysis, the integration of mathematical principles, and explores key modules and real-world applications of machine learning and deep learning across diverse domains

Program Overview

In recent years, empirical evidence has demonstrated that deep learning and machine learning methodologies consistently achieve significantly higher levels of accuracy compared to earlier approaches. These advancements are poised to influence various facets of computing, spanning data analysis, software engineering, and artificial intelligence. As a professional, possessing a robust comprehension of machine learning and deep learning is becoming increasingly essential. The Certificate Programme in Machine Learning and Deep Learning at IIT Delhi is meticulously crafted for individuals seeking practical expertise in addressing real-world challenges through the application of deep learning and machine learning techniques.

Course Content

  • Programming with Python

  • Foundations of Python Programming

  • Data Structures, Loops, and Control Structures

  • Functional Programming in Python

  • Linear Algebra using NumPy

  • Data Pre-processing using Pandas

  • Data Visualization using Matplotlib

  • Scikit-learn

  • Mathematical Foundations

  • Linear Algebra: Vectors, Matrices, Norms, Subspaces, Projections, SVD, EVD, Derivatives of matrices, Vector Derivative Identities, Least Squares

  • Optimization: Gradient Descent, Second Derivative Test, Constrained Optimization, KKT

  • Probability Theory: Discrete and Continuous Random Variables, Conditional Probability, Joint Probability Distribution, Multivariate, MAP Criterion, ML Criterion

  • Machine Learning and Neural Networks

  • Introduction to AI/ML/DL and Data Analysis

  • Linear Regression Model

  • Introduction: Supervised & Unsupervised Learning, Classification & Regression Models

  • Bayesian Decision Theory: Bayesian Classifier, Discriminant Functions, Minimum Error Rate Classification

  • Naïve Bayes Theory with Example

  • Logistic Regression Model

  • Parameter Estimation-Maximum Likelihood

  • Principal Component Analysis

  • Non-parametric Techniques: K-nearest Neighbor, Density Estimation

  • Decision Tree with Example (Entropy, Gini Impurity Index)

  • Perceptron, Multilayer Perceptron, LMS, Feedforward Operation, Backpropagation Algorithm, Activation Function, Loss Function, XOR Problem, Cross-validation, Regularization, Demonstration on Classification and Regression Applications

  • Radial Basis Functions and K-means Clustering

  • Support Vector Machine (SVM)

  • Random Forest, Ensemble Learning, Bagging, Boosting

  • Deep Learning

  • Basics of Deep Learning

  • Deep Learning Architectures: DNN, CNN, RNN, LSTM, Autoencoder

  • Methodology and Applications

  • Demonstration of Deep Learning Applications

  • Applications of Machine Learning

  • Computer Vision

  • Speech Recognition

  • NLP

Course Details

Mode of Study

Live Online with Campus Exposure

Class schedule

Saturday and Sunday: 10:00 a.m. to 12:00 p.m. (tentative)

Campus classes

1 day for interaction with candidates. (optional)

Duration of the Program

6 Months

Who this program is for?

  • Graduates from science or engineering background seeking a career in the ML/DL domain

  • Professionals in the software and IT industry seeking to upskill with ML/DL expertise and applying this intelligent learning tool in their respective fields

  • Professionals aspiring to work as data engineers, data scientists, machine learning engineers, etc.

Eligibility Criteria

Any science or engineering graduate with at least 1 year of experience

Selection Criteria

Selection based on application review.

Does this program comes with Alumni Status?

No

Important Dates

Application Deadline 4th Sep 2023
Program Start Date 30th Sep 2023

Fees Details

Application Fees 1,60,000 INR
Program Fees 1,60,000 INR

Fees Notes

*Registration fee of ₹10,000 will be charged for processing the selected applications only, post confirmation email from the institute. The registration fee is also part of the total programme fee. An offer letter from CEP, IIT Delhi will be released post the successful receipt of the Registration Fee. All fees should be submitted in the IITD CEP Account only, and the details will be shared post-selection by CEP IITD. **GST@ 18% will be charged extra in addition to the fee

Certificate Details

  • Candidates who score at least 50% marks overall and have a minimum attendance of 50%, will receive a ‘Certificate of Successful Completion’ from CEP, IIT Delhi.

  • Candidates who score less than 50% marks overall and have a minimum attendance of 50%, will receive a ‘Certificate of Participation’ from CEP, IIT Delhi.

  • The organising department of this programme is the Department of Electrical Engineering, IIT Delhi.

  • *Only e-certificates will be issued by CEP, IIT Delhi.

Sample Certificate

Key points about this program.

  • IIT Delhi is ranked #3 as per QS World University Rankings 2023 in India

  • 6-month online training programme for working professionals

  • 72 hours of live online teaching

  • IIT Delhi Continuing Education Programme (CEP) certificate

Apply By: 4th Sep 2023
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About the Institute

IIT Delhi promotes academic growth by engaging in cutting-edge research and offering state-of-the-art undergraduate, postgraduate, and doctoral programmes. With values focused on excellence in scientific and technical education and research, and reputed alumni who are leading scientists, technologists, business managers and entrepreneurs in various domains, IIT Delhi has contributed significantly to nation building and industrialisation.

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