Electronics & ICT Academy, IIT Guwahati

About the Course

A premium, compact certification crafted by IIT Guwahati Professors, Research Scholars and Staff. You will build portfolio-grade deliverables, receive 1:1 mentor feedback, participate in mock interviews and get research paper writing guidance from IIT Guwahati veterans.

Flexible learning: Recordings + weekly live sessions
Practical projects: Real company briefs with mentor reviews
Career support: Portfolio building & interview coaching
Research: Research paper writing assistance for higher studies

See features

Duration

7–8 hours weekly engagement through live, query and hands-on sessions. Total 4 semesters of three months each.

Tools

Python, Jupyter Notebook, Google Colab (GPU support), VS Code for development.

Career Prep

Resume building, portfolio preparation, mock interviews and interview strategy sessions.

Community

Active cohort groups with E&ICT Academy IIT Guwahati alumni network.

Activities

On-campus orientation and immersion at the beginning and completion of the program.

Capstone & Research

Showcase-ready capstone project and research paper writing guidance from IIT Guwahati veterans.

Why Choose Our Applied Machine Learning & Data Science Certification?

A program built to give you practical skills, industry relevance, and career growth.

Introduction to the Field

The world is driven by data. Industries across the globe are rapidly adopting Artificial Intelligence and Machine Learning to revolutionize operations, create new products, and drive strategic decisions. This rapid adoption has created a significant skills gap, offering immense career opportunities for those with the right expertise.

Key Benefits of This Certification

Practical & Applied Focus

Unlike theoretical programs, this certification emphasizes hands-on application, enabling you to build, deploy, and manage real-world AI/ML solutions.

Comprehensive Curriculum

From foundational mathematics and programming to Deep Learning, NLP, Computer Vision, and Cloud Deployment — gain a complete end-to-end skill set.

Expert-Led Training

Learn from industry practitioners and experienced academics who bring real-world insights into the classroom.

Career-Centric Approach

Career counseling, interview preparation, and a strong capstone project to enhance job readiness.

Four-Level Certification

Earn individual certificates after each semester to showcase progressive skill development.

Portfolio Building

Graduate with a strong portfolio, including a capstone project that demonstrates your expertise to employers.

Key Features

Designed to make you employer-ready and prepared for future studies.

Hands-on Learning

Project-based learning with real-world, portfolio-ready deliverables.

Dedicated Mentors

One-to-one mentor reviews and query assistance via email and live sessions.

Live Sessions

Weekly interactive sessions and masterclasses by eminent domain experts.

Certification

Industry-recognized certificates awarded after completion of each semester.

Eligibility

Open to professionals with 0+ years of experience. Applicants with demonstrable project work are preferred. Need-based scholarships available.

Next cohort:

April, 2026

Learning Path Visualization

Step-by-step path from fundamentals to capstone and research covering 15 detailed Modules.

Foundations

Initial 2 Modules of 90 Hours duration forming Semester I of the course.

Core Machine Learning

Intermediate 2 Modules of 90 Hours duration forming Semester II of the course.

Advanced ML & Deep Learning

Advanced 2 Modules of 90 Hours duration forming Semester III of the course.

NLP, Cloud & Final Project

Portfolio-grade final capstone project + mock interviews + Research Paper Writing.

Syllabus

Detailed module breakdown — expand to view topics and resources.

Module 101 Mathematics and Statistics: Delve into Linear Algebra, Multivariate Calculus, Statistics, and Probability. Learn Linear Regression, Outlier Rejection, and both Unconstrained and Constrained Optimization, including Stochastic Search with GA and PSO.

Module 102 Python Programming: Master Python Fundamentals, String Objects and Collections (Tuples, Set, Dictionaries, Functions). Get a thorough introduction to Pandas, covering basics, Series, Dataframes, text data, indexing, selecting, visualization, and critical data manipulation and cleansing techniques like handling missing values and skewness.

Module 201 Feature Space and Dimensionality Reduction, Unsupervised Learning, Generative Models, Pattern Mining: Gain proficiency with NumPy, SciPy, Scikit-learn, Seaborn, and Matplotlib. Understand the Machine Learning Task Workflow, Feature Space transformations, and separability. Explore Hashing Techniques for Feature Space Partition, Feature Subset Selection, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Exploratory Factor Analysis (EFA).

Module 202 Unsupervised Learning, Generative Models, Pattern Mining: Explore various Unsupervised Learning techniques including Adaptive Thresholding, K-Means, Hierarchical Agglomerative Clustering, DBSCAN, Nonparametric Estimation, and Mean-Shift Clustering. Learn Performance Analysis of Clustering Algorithms, Parametric Estimation (Bias, Variance, MLE), Learning Mixture Models, Unsupervised Representation Learning, Probabilistic Latent Semantic Model (PLSA), Association Rule Mining, Suffix Tree and Sequence Mining, Markov Process, Hidden Markov Model (HMM), and Prediction with Autoregressive Process Models.

Module 301 Supervised Learning- Classification and Regression: Dive into Supervised Learning with Bayesian Classification, Logistic Regression, Perceptron, Multilayer Perceptron, K-NN, RBF ANN, Classification & Regression Trees, Ensemble Methods, and SVMs.

Module 302 Deep Learning and Computer Vision: Introduction to CNNs, RNNs, LSTM, Encoder-Decoder Networks, GANs. Practical CV skills using OpenCV for Feature Extraction, Object Detection, Face Recognition, Object Tracking, and Image Segmentation in DL Frameworks.

Module 401 NLP, Speech and Audio Processing: NLP with NLTK (Tokenization, Lemmatization, Morphology), n-gram models, Word2Vec, GloVE, Neural Language Models, CNN/RNN for sequence labeling. Speech processing with LibRosa for feature extraction, recognition, and synthesis.

Module 402 ML on Cloud, Counselling and Final Project: Cloud fundamentals and ML tools on AWS, Azure, GCP. Career counselling, interview tips, Capstone project, and final presentation.

Course Mentors

Experienced practitioners from IIT Guwahati in this field.

Meet the Instructors

Instructors of this course are IIT Guwahati Research Scholars and Staff in this field.

Feroza Haque

Project Manager
E&ICT Academy, IIT Guwahati

Ms. Pronamika Buragohain

Project Engineer
E&ICT Academy, IIT Guwahati

Mr. Koushik Bharadwaj