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Post Graduate Program in AI and Machine Learning

2,388 Ratings

This Post Graduate program in AI and Machine Learning in collaboration with Microsoft is curated to upskill you in the field of AI and ML and make you an expert in this popular IT domain. Learn from top faculty at MNIT & Industry experts to master Artificial Intelligence, deep learning, neural networking, and other concepts in this domain.

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Learning Format

Online

Live Classes

12 Months

Career Services

by Intellipaat

Placement Assistance

Interviews

500+

Hiring Partners

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About PG in Artificial Intelligence and ML

Our Post Graduate program in AI and Machine Learning is conducted by MNIT, Jaipur faculty in an online instructor-led format to help you master basic and advanced-level skills in Artificial Intelligence and Machine Learning.

Key Highlights for PG Program in Machine Learning and AI

500 Hrs of Applied Learning
122 Hrs Self-paced Videos
80+ Live sessions across 12 months
50+ Hrs Project & Exercises
PG Certification by E&ICT Academy, MNIT
Resume preparation and LinkedIn profile Review
1:1 Mentor Support
24*7 Support
Live classes from MNIT faculty

About E&ICT MNIT, Jaipur

Electronics & ICT Academy MNIT, Jaipur (E&ICT MNIT, Jaipur) is an initiative supported by the Ministry of Electronics & Information Technology (MeitY), Govt of India. The courses provided by us emphasize bridging the gap between industry demand and academic approach to learning and providing a foundation to build your career in top IT companies.

In this Post Graduate program in AI and Machine Learning, you will:

  • Receive PG certificate from E&ICT, MNIT & Intellipaat
  • Receive live lectures from the MNIT faculty

Key Achievements of MNIT, Jaipur

  • Ranked 35 in NIRF 2020 Ranking among top engineering colleges
  • Ranked 23 by the Week in 2020 for engineering
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Program in Collaboration with Microsoft

Benefits for students from Microsoft:

  • Official study material from Microsoft
  • Industry-recognized certification from Microsoft
  • Real-time projects and exercises
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Who Can Apply for the Post Graduate Program in AI and Machine Learning?

  • Anyone keen to build a career in Machine Learning and AI
  • Professionals who wish to upgrade their skills
  • Developers aiming to gain expertise in the latest and most popular technologies
  • Software Engineers and Data Analysts
  • Machine Learning and Artificial Engineers who want to move ahead in their career
  • Freshers looking to master AI & ML domains
Who can aaply

What roles can an Artificial Intelligence & Machine Learning Professional play?

AI Expert

Develop strategies on numerous technologies and frameworks and come up with AI-based solutions for various business problems.

Research Engineer

Build robust optimization algorithms for several AI-based applications and services to help the business grow.

Senior Data Scientist

Figure out the various business problems created due to the data and solve those by developing data-based models.

Deep Learning Expert

Build new models with deep learning techniques, optimize and deploy them on GPUs, and implement them in the robotics software of the company.

Machine Learning Expert

Use a varied range of machine learning and artificial intelligence tools to create statistical models using business data.

NLP Engineer

Design, build, and implement NLP algorithms, use semantic modeling, and write scripts for performance analysis.

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Skills to Master

Machine Learning Models

Regressing Modeling

Classification Modeling

Random Forest

Decision Tree Models

K-means Clustering

Times-Series Prediction Model

Deep Learning

TensorFlow

Neural Networking

CuPy

Keras

PyTorch

NLP

Image Processing

Computer Vision

SQL

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Tools to Master

python jupyter tensorflow CuPy Keras PyTorch NLTK FastAPI Swagger Paperspace Postman TensorFlow_Lite TensorFlow_JS spark pyspark Streamlit SQL pandas SparkSQL ScrappingHub
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Meet Your Mentors

Curriculum for Post Graduate Program in AI and Machine Learning

Live Course Self Paced Industry Expert Academic Faculty

Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, and how you can use various IDEs for Python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling, etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 
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In this module, you will get acquainted with the various libraries and functions in Python to help you understand data science and machine learning concepts better.

2.1 PySpark
2.2 Python
2.3 NumPy
2.4 SciPy
2.5 Matplotlib
2.6 Pandas
2.7 Python script
2.8 Python variable

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Tools covered

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3.1 Regression Modeling: Logical and Linear
3.2 Classification Modeling: K-nearest neighbor, Naïve Bayes Theorem, and Support Vector Machines (SVM)
3.3 Random forest and decision tree models
3.4 Use of PCA, k-means clustering, and isolated forests for anomaly detection
3.5 Time-series prediction model and recommendation system
3.6 Selection, evaluation, and interpretation of models

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Tools covered

Tools Covered Tools Covered

4.1 Introduction to neural networking
4.2 Backpropagation
4.3 Stochastic gradient descent
4.4 Deep neural networking and its principles
4.5 CNNs, RNNs, LSTMs, and MLPs
4.6 GANs and Generative deep learning
4.7 Calculus and linear algebra
4.8 TensorFlow, CuPy, Keras, and PyTorch

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Tools covered

Tools Covered Tools Covered Tools Covered Tools Covered

5.1 Natural Language Processing (NLP) and text mining

  • Introduction NLP & text mining
  • Applications of text mining
  • How NPL works with text mining
  • Natural Language Toolkit (NLTK) environment

5.2 Data cleaning and Preprocessing

  • Various tokenizers and Tokenization
  • Frequency distribution
  • Stemming, POS tagging, and lemmatization
  • Bigrams, Trigrams, and Ngrams
  • Entity recognition

5.3 Classification of text

  • Overview of Machine Learning
  • Words, term frequency, and count vectorize
  • Inverse document frequency, text conversion, and confusion matrix
  • Naive Bayes Classifier

5.4 Sentence structuring, language modeling, sequence tagging, and sequence tasks

  • Language modeling, sequence tagging, and sequence tasks
  • Predicting the sequence of tags
  • Syntax trees
  • Context-free grammar
  • Chunking
  • Automatic paraphrasing of texts

5.5 Vector space models and semantics

  • Distributional semantics
  • Traditional and topic models
  • Tools for sentence and word embeddings

5.6 Dialog systems

  • Introduction to task-oriented dialog systems
  • Natural language understanding
  • Dialog Manager
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Tools covered

Tools Covered

6.1 Basics of computer vision and OpenCV
6.2 Use of neural networking for image processing
6.3 Classification and clustering of an image using GANs, multitask classifiers, and k-means
6.4 Detection of object
6.5 Image segmentation
6.6 Computer vision trends

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7.1 Development of large-scale AI apps using various tools and techniques
7.2 Build and deploy APIs with FastAPI, Swagger, Paperspace, and Postman
7.3 CI/CD pipeline for model production
7.4 Use of TensorFlow Lite, TensorFlow.js, and Streamlit to package model
7.5 Model production using PyTorch, Spark, and PySpark

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Tools covered

Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered

8.1 Data collection from RSSs, web scraping, and APIs
8.2 Data cleaning and transformation for ML systems
8.3 Automatic transformation tools
8.4 SQL and NoSQL databases to deal with large sets of data
8.5 Spark
8.6 Pandas
8.7 SQL and Spark SQL
8.8 ScrappingHub

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Tools covered

Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered Tools Covered

Upon completion of the AI and ML course, you can culminate your Machine Learning and AI skills through a real-world industry-based capstone project that aims to make you use all the skills that you have gained in the program.

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10.1 Introduction to R
10.2 R packages
10.3 Sorting DataFrame
10.4 Matrices and vectors
10.5 Reading data from external files
10.6 Generating plots
10.7 Analysis of Variance (ANOVA)
10.8 K-means clustering
10.9 Association rule mining
10.10 Regression in R
10.11 Analyzing the relationship with regression
10.12 Advanced regression
10.13 Logistic Regression
10.14 Advanced Logistic Regression
10.15 Receiver Operating Characteristic (ROC)
10.16 Kolmogorov-Smirnov chart
10.17 Database connectivity with R
10.18 Integrating R with Hadoop

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11.1 Introduction to Git
11.2 Architecture of Git
11.3 Working with remote repositories
11.4 Branching and merging
11.5 Git methodology
11.6 Git plugin with IDE (Eclipse)

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  • Job Search Strategy
  • Resume Building
  • LinkedIn Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.
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Disclaimer
Intellipaat reserves the right to modify, amend or change the structure of module & the curriculum, after due consensus with the university/certification partner.

Program Highlights

150 Hours of live training
122 Hours of Self-paced video
232 Hours of Guided projects
24/7 Lifetime support

Project Work

Projects will be a part of your PG Certification in Artificial Intelligence and Machine Learning to consolidate your learning. It will ensure that you have real-world experience in Data Science and ML

Hear From Our Hiring Partners

Career Services By Intellipaat

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions and that will help you stay on track with your up skilling objective.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

One-on-One Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Our Alumni Works At

Master Client Desktop

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, and make new friends – the possibilities are endless and our community has something for everyone!

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hackathons
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collaborative-learning

Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

Submit Application

Submit Application

Tell us a bit about yourself and why you want to join this program

Application Review

Application Review

An admission panel will shortlist candidates based on their application

Admission

Admission

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

$ 1,799

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Upcoming Application Deadline 23rd Mar 2024

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 23rd Mar 2024 08:00 PM IST Weekend (Sat-Sun)
Regular Classes 23rd Mar 2024 08:00 PM IST Weekend (Sat-Sun)

FAQs on Post Graduate Program in AI and Machine Learning

Who will conduct the training in this PG program in Machine Learning and AI?

Subject matter experts from MNIT, Jaipur, and specialists from top industries will teach you all the basic and advanced level concepts in the field of Machine Learning and Artificial Intelligence. This PG in Artificial Intelligence and Machine Learning will make you an expert and help you acquire all the necessary skills to land a high-income job at a reputed organization.

Intellipaat provides career services that include Guaranteed interviews for all the learners enrolled in this course. EICT MNIT Jaipur is not responsible for the career services.

The trainers of this Machine Learning and Artificial Intelligence training program go through a rigorous selection process in order to make your PG in Machine Learning and AI smooth by assigning the best trainers.

The program is conducted in an online format by expert professionals from E&ICT Academy and MNIT, Jaipur.

You will work on numerous industry-grade projects which will substantiate your learning and provide real-world experience.

The entire post graduate program will be completed over the span of nine months wherein you will learn all the courses and successfully complete the projects.

To be eligible for getting into the placement pool, the learner has to complete the course along with the submission of all projects and assignments. After this, he/she has to clear the Placement Readiness Test (PRT) to get into the placement pool and get access to our job portal as well as the career mentoring sessions.

Please note that the course fees is non-refundable and we will be at every step with you for your upskilling and professional growth needs.

Due to any reason you want to defer the batch or restart the classes in a new batch then you need to send the batch defer request on [email protected] and only 1 time batch defer request is allowed without any additional cost.

Learner can request for batch deferral to any of the cohorts starting in the next 3-6 months from the start date of the initial batch in which the student was originally enrolled for. Batch deferral requests are accepted only once but you should not have completed more than 20% of the program. If you want to defer the batch 2nd time then you need to pay batch defer fees which is equal to 10% of the total course fees paid for the program + Taxes.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work