Postgraduate Program In Machine Learning And Artificial Intelligence
Become a machine learning and artificial intelligence expert with a job assurance program
Weekday
Classroom & Live Online Training
9 Months Program
300+ Learning hours
25+ Projects
10+ Tools
15000+
Students Placed
22.5LPA
Highest Salary
52%
Average Salary Hike
2000+
Hiring Partners
15000+
Students Placed
22.5LPA
Highest Salary
52%
Average Salary Hike
2000+
Hiring Partners
Our Alumni Work At
Join The Best Machine Learning And Artificial Intelligence Course
Learn how to develop machine learning models from the ground up and use them to create AI solutions. This job assurance program is for working professionals (with up to 5 years of experience) who want to build a data science, machine learning, or artificial intelligence career. With a comprehensive learning track, you'll learn SQL application, Python, Machine Learning, and Data Visualisation with Tableau.
100% Job Assurance
Our data science course comes with a job assurance that offers you 10 guaranteed interviews at over 500 top-tier partner organisations hiring data science and analytics professionals.
Job-specific Curriculum
Learn the practical applications of data science, Python, SQL, data analytics, power BI, and tableau while gaining expertise in these subjects.
Live Learning Module
Our expert faculty delivers our robust curriculum using an interactive module and hands-on training methods to prepare you to work in various data science roles.
Real-world Projects
Implement what you’ve learned with over 25 real-world projects and case studies specially formulated by industry experts to make you job-ready.
Dedicated Career Services
Our career services include resume development, profile enhancement, career mentorship, job assurance workshops and one-on-one career counselling to ensure you land the right job.
Imarticus COE Organised Hackathons
Make your resume stand out by participating in coding hackathons to tackle complex business problems and get an opportunity to compete in a national-level competition.
Trusted By Millions Of Learners Around The World
Curriculum
A progressive curriculum and learning methodology make our program ideal for those seeking positions in top companies requiring artificial intelligence and machine learning skills.
Foundation
We’ve added a foundation module for those who have no programming knowledge.
The module covers the basics of programming for non-programmers. Learn programming concepts and implement those concepts to write efficient code. Get introduced to Lists and OOPS concepts.
What Will You Achieve?
Build a solid foundation for programming
Practice coding skills with 20+ coding questions
Topics
Introduction to Programming
Variables & Arithmetic Expressions
Functions
Data Types
Conditions and Conditional statements
Lists
OOPS
Core Track
Learn the principles of data science, machine learning and python programming in the core track.
The module covers the basics of Excel for data science. Learn Excel essentials to get strong hold on using Excel for data analysis. Get introduced to pivot tables, formulae and charts.
What Will You Achieve?
Build strong foundation of Excel for data analysis
Summarise data with pivot tables and charts
Topics
Pivot tables, Charts and Look up
The module introduces learners to SQL programming. Learn how to query data from the databases and create datasets for data analysis.
What Will You Achieve?
Build a strong SQL foundation for data querying
Create datasets for data analysis
Topics
Introduction to SQL
DDL Statements
DML Statements
DQL Statements
Aggregate Functions
Date functions
Union, Union All & Intersect Operators Joins
Views & Indexes
Sub-Queries
The module introduces the learners to Python programming. Work with multiple Python data science libraries to execute essential tasks like mathematical calculations, data manipulation, etc. Learn data visualisation with Python.
What Will You Achieve?
Master Python programming
Run data analysis process using Python libraries
Create useful charts for data visualisation
Topics
Python Introduction
Variables
Functions
Python Operators
Python Flow Controls
Conditional Statements
Loops
User defined Functions
Function Arguments
Lamda Functions
Introduction to NumPy
NumPy Array
Creating NumPy Array
Array Attributes
Array Methods
Array Indexing
Slicing Arrays
Array Operation
Iteration through Arrays
Introduction to Pandas
Pandas Series
Creating Pandas Series
Accessing Series Elements
Filtering a Series
Arithmetic Operations
Series Ranking and Sorting
Checking Null Values
Concatenate a Series
Pandas Dataframe - Introduction
Dataframe Creation
Reading Data from Various Files
Understanding Data
Accessing Dataframe Elements using Indexing
Dataframe Sorting
Ranking in Dataframe
Dataframe Concatenation
Dataframe Joins
Dataframe Merge
Reshaping Dataframe
Pivot Tables
Cross Tables
Dataframe Operations
Checking Duplicates
Dropping Rows and Columns
Replacing Values
Grouping Dataframe
Missing Value Analysis & Treatment
Visualisation using Matplotlib
Plot Styles & Settings
Line Plot
Multiline Plot
Matplotlib Subplots
Histogram
Boxplot
Pie Chart
Scatter Plot
Visualisation using Seaborn
Strip Plot
Distribution Plot
Joint Plot
Violin Plot
Swarm Plot
Pair Plot
Count Plot
Heatmap
Summary Statistics
Missing Value Treatment
Dataframe Analysis using Groupby
Advanced Data Explorations
The module introduces the learners to statistics. Review, analyse, and draw conclusions from data. Apply quantified mathematical models to appropriate variables for data analysis.
What Will You Achieve?
Build a strong foundation for Statistics
Analyse data and draw conclusions using statistics
Implement mathematical models for data analysis
Topics
Introduction to Statistics
Random Variables
Descriptive Statistics
Measure of Central Tendency
Measure of Dispersion
Skewness and Kurtosis
Covariance and Correlation
What is Probability?
Events and Types of Events
Sets in Probability
Probability Basics using Python
Conditional Probability
Expectation and Variance
Probability Distributions
Discrete Distributions
- Uniform
- Bernoulli
- Binomial
- Poisson
Continuous Distributions
- Uniform
- Normal
Probability Distributions using Python
Introduction to Hypothesis Testing
Terminologies used in Hypothesis Testing
Procedure for testing a Hypothesis
Test for Population Mean
Small Sample Tests
Large Sample Tests
Test for Normality
One-way ANOVA
Assumptions
ANOVA Hypothesis
Post Hoc Test
Chi-Square Test
Chi-Square Test Steps
Chi-Square Example
The module introduces the learners to machine learning and explains how different ML algorithms work. It also covers optimisation of models and model tuning. Get a complete understanding of how organisations are applying ML to solve their problems and grow the business.
What Will You Achieve?
Analyse data and make predictions
Solve real-world business problems using ML
Deploy ML model on Cloud
Topics
Introduction to Machine Learning
Machine Learning Modelling Flow
Parametric and Non-parametric Algorithms
Types of Machine Learning
Introduction of Linear Regression
Types of Linear Regression
OLS Model
Math behind Linear Regression
Decomposition Variability
Metrics to Evaluate Model
Feature Scaling
Feature Selection
Regularisation Techniques
Project - Property Price Prediction
Class Assessment on Linear Regression
What is Optimisation?
Gradient Descent
Adagrad Algorithm
Adam Algorithm
Prerequisites
Introduction to Stochastic Gradient Descent (SGD)
Preparation for SGD
Workflow of SGD
Implementation of SGD on Linear Regression
Classification with Linear Regression
Intro to Logistic Regression
Maximum Likelihood Estimation
Logistic Regression Using SGD
Performance Metrics
Introduction to Decision Tree
Entropy
Information Gain
Greedy Algorithm
Decision Tree: Regression
Gini Index
Tuning of Decision Tree
Introduction to Random Forests
Averaging
Bagging
Random Forest – Why & How?
Feature Importance
Advantages & Disadvantages
Project - Taxi Fare Prediction
Class Assessment on Classification
What is Clustering?
Prerequisites
Cluster Analysis
K-means
Implementation of K-means
Pros and Cons of K-means
Application of K-means
Project - E-commerce Customer Segmentation
Introduction to Hierarchical Clustering
Types of Hierarchical Clustering
Dendrogram
Pros and Cons of Hierarchical Clustering
Project - Travel Review Segmentation
Home Assignment on Clustering
Prerequisites
Introduction to PCA
Principal Component
Implementation of PCA
Case study
Applications of PCA
Project - Real Estate Data Analysis using PCA
Understand Time Series Data
Visualising Time Series Components
Exponential Smoothing
Holt's Model
Holt-Winter's Model
ARIMA
Project - Forecasting the Sales of a Furniture Store
Basics of Cloud
Machine Learning on Cloud
Deploying ML models on Cloud
The module covers data visualisation with two popular business intelligence tools - Tableau and Power BI. Create charts to articulate data and present insights to the business. Learn to showcase a data-based story to the stakeholders.
What Will You Achieve?
Master data visualisation with Tableau
Create meaningful dashboards for the business
Topics
Introduction to Tableau
Data Connection
Tableau Interface and Basic Chart Types
Working with Metadata
Visual Analytics
Mapping
Calculations
Dashboard and Stories
Specialisation Track
At the end of the core module, we will evaluate your performance and assign a specialisation track with dedicated project mentors for optimal learning.
Sharpen ML skills through projects
Learn advanced ML skills
Get introduced to AI
What is Ensembling?
Bootstrap Method
Bagging
Boosting
XGBoost
AdaBoost
Some detailed project based on Classification
Association Rules - Apriori algo
Market Basket Analysis - Problem
Some detailed project based on RFM model
Convolutional Neural Network
Architecture of Convolutional network
Image as a Matrix
Convolutional Layer
Feature Detector & Feature Maps
Pooling Layer and Max pooling
Flattening Layer
Padding
Striding
Image Augmentation
Basics of Digital Images
What is Computer Vision
Image Formation
Image Processing – flipping, cropping, rotating, scaling
Drawing on images
Image statistics & Histogram
Spatial Resolution
Gray level/Intensity Resolution
Convolution
Smoothing, Sharpening
Color Space Conversion & Histogram
Thresholding for Binarization
Sobel’s Edge Detection Operator
Image Feature – Key-point and Descriptor
Stream Video Processing with OpenCV
Transfer Learning – Introduction and Motivation
Transfer Learning –ConvNet
A Transfer Learning Scenario
ILSVRC
ImageNet
VGGNet (VGG16)/Inception/ResNet
Project using Transfer Learning Model
Introduction to RNN
RNN Network Structure
Different Types of RNNs
Bidirectional RNN
Limitations of RNN
What is NLP?
Sentence Segmentation & Tokenization
Stemming, Lemmatization
Part of Speech – POS
Named Entity Recognition (NER)
Parsing, Chunking
Stop Words Removal (English)
Corpora/Corpus
Context Window – Bi-gram, N-gram
Applications of NLP
Introduction to the NLTK Library
Processing Raw Text
Normalizing Text
String Processing with Regular Expression
Extracting Features from Text
Bag-of-Words(BoW), TF-IDF
Intro to Gensim
LDA-Latent Dirichlet Allocation
NMF-Non negative Matrix Factorization
Intro to knowledge graph
Project using Topic Modelling(unsupervised text data)
Build a data science project on your own by applying the learning from the bootcamps. Learn planning the project and implementing it successfully. Present your project to a team of evaluators from the industry and get valuable feedback. Add the project to you GitHub project portfolio.
What Will You Achieve?
Learn to plan a data science project
Solve a real-world problem using data science
Gain confidence on your skills by presenting the project to industry experts
Topics
Combination of all skills learned throughout the course
Project Presentation Skills
Prepare for interview opportunities by polishing the key skills. Get support to create your digital profile and resume. Sharpen your interview skills through interview preparation workshops and expert-based mock interviews. Resolve your career-related queries through career mentorship session. At the end of the module, you will be ready for real interviews.
What Will You Achieve?
Build an exciting resume and digital profile for recruiters
Sharpen interview skills with mock interview sessions
Resolve any career related queries to have clarity and confidence
Topics
Resume-building
GitHub Project Portfolio
Interview Preparation
Mock Interviews
Career Mentorship
Gain expertise in data analysis, visualisation, storytelling, and problem-solving.
Enhance strong communication, presentation, interpersonal skills, and critical thinking.
PowerPoint for Corporate
Canva- Designing
Problem Solving- Guesstimates
Mastering Fundamentals of Excel
The Art of Storytelling Using Excel
Art of storytelling using PowerBI
What is Data Science & Importance of Data
Exploratory Data Analysis
Introduction to Machine Learning
Data Storage & fundamentals of Databases
Python Bootcamp - Start Your Tech Adventure
Nonverbal cues - Body Language, which is very vital for interview purposes
Personality Development and Confidence Building
FAQs - Interview Prep - Throwing some insights on how to answer these questions
Word Power and Vocabulary Building
SMART Technique for Productivity
Hiring Partner's Quote
To appreciate your efforts for finding us the best of candidates for our Data Science team here in trinity mobility....see more
My sincere gratitude towards the service rendered as Learners primary skillset a...see more
The capacity to learn is a gift, The ability to learn is a skills,The willingness to learn is a choice! And that choice is given by Imarticus learning...see more
Analytics Centre of Excellence
Analytics Centre of Excellence
Get Ready with exclusive sessions, hackathon, project competition and webinar by Imarticus Learning
The high impact benefits that you get at the Centre of Excellence by Imarticus Learning:
Data Wars Hackathons
Data Dive Webinars
Data Verse Projects
Data Fluent Seminars
Data Decisions Roundtables
Projects That You will Work On
Get an opportunity to work on real-world projects, and case studies that will give you an overview of the data science and machine learning fields and provide you with the necessary technical skills. Some of the indicative projects are:
Projects That You Will Work On
Get an opportunity to work on real-world projects, and case studies that will give you an overview of the data science and machine learning fields and provide you with the necessary technical skills. Some of the indicative projects are:
Will I Get Certified?
Upon successfully completing this program, you’ll earn a Postgraduate Program in Machine Learning and Artificial Intelligence certificate. This certification will add considerable value to your professional credentials.
What Can I Become?
Data Scientist
Data Analyst
Business Analyst
Business Intelligence Specialist
Business Analytics Professional
Analytics Manager
Data Science Consultant
Machine Learning Engineer
Data Scientist : A data scientist gathers, analyses and interprets large amounts of data. They develop statistical and predictive models and require high-level strategic and analytical skills.
Grow With Imarticus Learning
We’re focused on giving you an integrated learning experience. With our one-of-its-kind career support services, we continue to support you as you take a step into your career with a renewed perspective. Get access to over 500+ placement partners and explore unlimited opportunities.
An In-Depth Look At The Data Science Job Landscape
Download Report
100% Job Assurance
Our career services will introduce you to existing artificial intelligence and machine learning job assistance opportunities.
Profile Enhancement
We assist you in building a robust portfolio to ensure that your profile always catches the eye of prospective employers.
Resume Building
Redesign your resume with professional help and highlight your strengths in the best possible way.
Interview Prep
We’ve analysed the most commonly asked interview questions and built a training module that will help you crack job interviews.
Career Mentoring
Our dedicated program mentors are seasoned professionals that will assist you with the curriculum, ensure you are up-to-date with in-class happenings and motivate you to move ahead in your academic journey.
#10 Guaranteed Interviews
Imarticus Data Wars Hackathon
Participate in the national-level data science hackathon
Compete to solve a challenging data science problem
Sharpen your data science application skills
Enhance your CV by winning the hackathon
Top 3 Hackathon Winners
Imarticus Data Verse Project Competition
Participate in the national-level data science competition
Create a data science project and nominate it for competition
Showcase your data science skills for real-world applications
Enhance your CV by winning the project competition
Top 3 Project Competition Winners
Transform Your Career With Imarticus
Imarticus Learning has placed more than 56,000 students in various industries.
Build Your Success Story With Imarticus
Program Fee
₹ 1,98,000
(Inclusive of all taxes)
Instalments
EMI Options
Registration Fees
₹ 10,000
Instalment 1
₹ 75,200
Instalment 2
₹ 56,400
Instalment 3
₹ 56,400
Moments Of Honour
FAQs
Companies will pay you up to Rs. 17 LPA if you have a solid background in AI and at least 2-3 years of relevant professional experience.
The median wage range for an AI expert with 4–8 years of experience is between R 35–50 lakh per year.
Artificial intelligence engineers with more than ten years of expertise can make more than one crore each year.
This PG program is a thoroughly engaging, full-time course dedicated to helping you get a high-paying job opportunities in the Machine Learning and AI industry. The faculty will cover every Data Science, Machine Learning and AI concept from scratch, and help you practice the application of these skills with rigorous real-world business projects throughout the course. You will participate in multiple discussions with your peers and share knowledge with each other. All your academic queries will get resolved during live sessions. Your Program Manager will support you throughout your learning journey to ensure you meet your career objectives.
The program has a Core Track and a Specialisation Track for effective learning. The Core Track starts with the basics of SQL, Python programming and statistics for data science. Once you have built a strong foundation, we will teach you data science techniques and applications. We will cover machine learning and deep learning and AI techniques, along with real-world projects to help you master the topics. Once you finish the Core Track, we will evaluate your acquired skills and assign one of the specialisation tracks to you.
The specialisation track will prepare you for specific job roles by polishing the required skills further. We will provide personalised learning through dedicated Project Mentors who will guide you to solve multiple projects and become an expert. Our specialisation track is very powerful for placement conversions. Personalised learning helps our students stand out in the crowd and get the best job opportunity.
We will also prepare you for placement opportunities through soft skill sessions, interview preparation workshops, career mentoring, and mock interviews. In order to truly boost your skills, we will organise a competitive Hackathon, where multiple aspirants across India will participate and compete with each other. You will also get the opportunity to participate in our national-level Data Science Project Competition by building an application-based data science project. Each critical element of the program will be graded and your performance will be closely monitored.
- Grades should be at least 40%
- Pass all Imarticus mock interviews and the capstone project evaluation
- Have an average attendance of at least 80% for each module
Attend multiple interview opportunities with our hiring partners to grab the most suitable job for you.
Resume-building:Redesign your CV to create the best profile and get noticed by hiring managers of your dream job interviews.
Profile enhancement:Enhance your profile with a GitHub project portfolio and Hackathon results.
Interview preparation workshop:Learn best practices and attend mock interviews with our industry experts to ace real interviews.
Career mentoring:Resolve all your career-related queries in 1:1 sessions with industry experts.