Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery | Frequency Of Classes |
|---|---|---|---|
| English | Self Study, Virtual Classroom, Campus Based/Physical Classroom | Video and Text Based | Weekends |
Course Overview
The PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification by the TalentSprint in collaboration with IIT Madras is a 12-month online course. This online certification course is designed to develop learners’ tech capabilities while enabling them to apply their learnings to make data-oriented business decisions for their organizations. The PG Level Advanced Programme in Applied Data Science and Machine Intelligence online course is designed and delivered by the Robert Bosch Centre for Data Science and AI (RBCDSAI) at IIT Madras.
The PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification syllabus discusses various important topics of data science and machine learning. The curriculum also includes capstone projects including recommendation systems, digital recognition systems, healthcare analytics, biological network analysis, and others. Participants can attend the PG Level Advanced Programme in Applied Data Science and Machine Intelligence classes through faculty-led interactive masterclass lectures, hands-on labs, and workshops. They will also visit the campus for three days towards the end of the cohort.
The Highlights
- 12 months online course
- Delivered by IIT Madras
- Hands-on curriculum & capstone projects
- Certificate of completion
Programme Offerings
- Online Course
- Hands-on Curriculum
- Masterclass Lectures
- Capstone Projects
- Mentor Support
- hackathons
- workshops
- Industry interactions
- 3-day campus visit
- Dedicated career assistance
- Certification
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Madras (IITM) |
The PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification fee is Rs 300,000. Participants can pay the course fee with zero per cent EMI by choosing their instalment options for a maximum of 48 months. For more details about EMI options, visit https://iitm.talentsprint.com/adsmi/fee.html.
With the scholarship, the PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification fee will be Rs 225,000.
PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification fee structure
Description | Amount in INR |
Total fee | Rs 300,000 |
With scholarship | Rs 225,000 |
Eligibility Criteria
Candidates seeking admission to the PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification course by TalentSprint in collaboration with IIT Madras must hold a B.E./B.Tech/B.Sc./M.E./M.Tech/M.Sc or an equivalent degree.
Work Experience
Candidates are required to have a minimum of 1 year of experience to pursue the PG Level Advanced Programme in Applied Data Science and Machine Intelligence online course.
What you will learn
The PG Level Advanced Programme in Applied Data Science and Machine Intelligence training will provide students with the foundational concepts of data science and machine learning. Students will also be able to:
- Build advanced tech capabilities and implement their learnings to make data-driven decisions for the growth of their organizations.
- Become familiar with data science concepts, and machine learning foundations & algorithms.
- Understand deep learning foundations & algorithms and their real-world use cases in industries along with associated challenges.
Who it is for
The PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification by TalentSprint in collaboration with IIT Madras is best suited for
- Individuals holding B.E./B.Tech/B.Sc./M.E./M.Tech/M.Sc or an equivalent degree.
- Professionals such as engineers, data analysts, software engineers, software developers, and others.
Admission Details
The admission process for the PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification course includes the following steps.
Step 1: Visit the official webpage - https://iitm.talentsprint.com/adsmi/
Step 2: Apply for the course
Step 3: Wait for selection
Step 4: Pay the remitting registration fee to block your seat
Step 5: Pay the full programme fee to enrol for the course
Step 6: Start learning
The course selection will be done by IIT Madras. The selection will be strictly based on the eligibility criteria and the inclination of applicants as expressed in their statement of purpose.
The Syllabus
- Linear Algebra for Data Science
- Linear equations and solutions
- Matrices and their Properties
- Eigenvalues and eigenvectors
- Matrix Factorizations
- Inner products
- Distance measures
- Projections
- Notion of hyperplanes
- Halfplanes
- Probability and Statistics for Data Science
- Probability theory and axioms
- Random variables
- Probability distributions and density functions
- Expectations and moments
- Covariance and correlation
- Statistics and sampling distributions
- Hypothesis testing of means, proportions, variances and correlations
- Confidence intervals
- Correlation functions
- Parameter estimation – MLE and Bayesian methods
- Optimization for Data Science
- Unconstrained optimization
- Necessary and Sufficiency conditions for optima
- Gradient descent methods
- Constrained optimization, KKTConditions
- Introduction to least squares optimization
- Bayesian decision theory, K-Nearest Neighbors
- Linear Regression, Ridge, LASSO
- Linear Classification (Logistic Regression, Linear Discriminant Analysis)
- Recap K-NN; Bias Variance tradeoff, cross-validation/ model selection
- Evaluation methods (ROC, AUC, F-measure, etc.)
- Naive Bayes, Decision tree
- Ensemble Methods: Bagging, Random Forest, Gradient
- Perceptron, Intro to Support Vector Machines
- Clustering motivation, K-means/Hierarchical, GMM
- Dimensionality reduction, Association Rule mining
- Industry Use case – Health care with NLP
- Use cases from the healthcare domain where NLP is applied
- Automatic case-correction of all-caps or all-small text from EMRs.
- Automatic token splitting of conjoined words and sentences.
- NER on EHRs
- Table detection and extraction of EOBs and EHRs.
- Computer-assisted medical coding of EHRs.
- Models such as Bi-LSTM-CRF, CAML, HAN, ResNexT.
- Public domain datasets - MIMIC-III.
- Use cases from the healthcare domain where NLP is applied
- Use cases in Systems Biology & Health care
- Introduction to big data in biology
- Levels of omics data, basic information flow in biology
- Importance of Networks in Biology: Overview
- Introduction to Network Science
- Learning from Network structure: Predicting essential genes
- Learning on Networks: Community detection to identify disease genes - Learning using Networks: Graph mining for predicting biosynthesis routes - Omic data
- Use case
- Problem Statement : Four case studies will be demonstrated.
- CS1: Choice of mode
- CS2: Travel time estimation
- CS3: Accident hot spot analysis
- CS4: Accident severity modelling
- Model(s) intended to demonstrate : Logistics regression, Support vector regression, k-means clustering and random forest
- Dataset to be used during the demo 4. Dataset for the mini project
- Problem Statement : Four case studies will be demonstrated.
- Use cases in Systems Biology & Health care Introduction to big data in biology
- Levels of omics data, basic information flow in biology
- Genomics, Transcriptomics, Epigenomics, Proteomics and Multi omics - Identification human disease genes using genomics
- Application of transcriptomics for identifying disease mechanisms
- Clinical data - kinds of clinical data Garbhini dataset - a clinical data case study
- Artificial Neural Networks
- Artificial Neuron
- Multilayer Perceptron
- Universal Approximation Theorem
- Backpropagation in MLPs
- Backprop on general graphs
- Optimization in Neural Networks
- Gradient Descent and its variants
- Momentum, Adam, etc.
Batch Normalization
- Basics of Hyper parameter optimization
- CNN - Part 1 and Part 2
- Introduction
- CNN Operations
- CNN Training
- Illustrative Example (“Hello World”) - MNIST digit classification
- Image Recognition-SoTA model(s)
- Object detection/localization - SoTA model(s)
- Semantic segmentation -SoTA model(s)
- RNN/LSTM
- Explainable Modes of DNN
- DL Use Cases
- Smart Cities
- Industry Use case 1
- Climate Science
- Manufacturing
- Bio-informatics
- Industry Use case 2
Instructors
IIT Madras (IITM) Frequently Asked Questions (FAQ's)
Candidates who have completed B.E./B.Tech/B.Sc./M.E./M.Tech/M.Sc or an equivalent degree can apply for this online certification course.
The duration of the PG Level Advanced Programme in Applied Data Science and Machine Intelligence certification course is 12 months.
Yes, you must have at least one year of experience to pursue this online certification course.
Yes, programming knowledge is required for the PG Level Advanced Programme in Applied Data Science and Machine Intelligence online course.
You can attend the classes through interactive masterclasses lectures, hands-on labs, workshops and a 3-day campus visit for enhanced learning.