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This PG course in Artificial Intelligence and Machine Learning is curated to upskill you in the field of AI and ML and make you an expert in this popular IT domain. Top faculty from MNIT & Industry experts will help you master the skills required to excel in Artificial Intelligence, deep learning, neural networking, and other concepts in this domain. This course is designed in collaboration with IBM & Microsoft to offer relevant industry experience.
In collaboration with
Upskill for Your Dream Job
Learning Format
Online
Live Classes
12 Months
E&ICT MNIT Jaipur
Alumni status
3 Guaranteed
Interviews
500+
Hiring Partners
About Program
Our AI and ML training course is an online instructor-led program whose main goal is to make you an expert in basic and advanced-level concepts and techniques in Artificial Intelligence and Machine Learning.
Free Career Counselling
We are happy to help you 24/7
About E&ICT MNIT, Jaipur
Electronics & ICT Academy MNIT, Jaipur(E&ICT MNIT, Jaipur) is an initiative supported by 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 program, you will:
Key Achievement of MNIT, Jaipur
About IBM & Microsoft
IBM and Microsoft are two of the biggest names and leading innovators when it comes to Machine Learning and Artificial Intelligence tools. The course is led by some of the experts who will take you through all the crucial concepts and essential skills required in the domain and get you started on projectsRead More..
Benefits for students from this IBM and Microsoft collaboration:
Develop strategies on numerous technologies and frameworks and come up with AI-based solutions for various business problems.
Build robust optimization algorithms for several AI-based applications and services to help the business grow.
Figure out the various business problems created due to the data and solve those by developing data-based models.
Build new models with deep learning techniques, optimize and deploy them on GPUs, and implement them in the robotics software of the company.
Use a varied range of Machine Learning and Artificial Intelligence tools to create statistical models using business data.
Design, build, and implement NLP algorithms, use semantic modeling, and write scripts for performance analysis.
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
A fellow of IETE and Sr. member of IEEE, he has 100+ research papers and chapters in reputed journals. He has guided 10 PhD theses and many UG/PG dissertations. His research area includes Trust, Integrity & Resilience in Hardware, pedagogy etc.
With best Ph.D thesis (IIT Roorkee) and IEI Young Engineers awards, he has research interest in Digital,Adaptive and Seismic Signal Processing, Data Clustering,etc. A Sr. member of IEEE, he has several awards & accolades in his name.
Suresh is responsible for overseeing and directing Big Data and Analytics projects at Microsoft. He is experienced in advanced analytics and big data, prescriptive and predictive analysis having expertise in Hadoop and Spark.
Manigandan has 16+ years of experience in cloud projects for Fortune 500 companies. He comes with a strong background in architecture and implementation of AWS, Azure, GCP, along with a hands-on experience in DevOps tools.
A Blockchain expert, David has been bringing integrated blockchain, particularly Hyperledger, Ethereum and Big Data solutions to the cloud. He has previously worked on Hadoop, AWS Cloud, Big Data and Pentaho Projects.
Module 1 - Preparatory Classes on Python for AI & ML
In this module you will master Python concepts and skills required to excel in AI & ML. This includes Python libraries, such as NumPy, SciPy, Matplotlib, etc., along with Python objects, classes, and more.
Module 2 - Machine Learning Models for Selection and Tuning
2.1 Regression Modeling: Logical and Linear
2.2 Classification Modeling: K-nearest neighbor, Naïve Bayes Theorem, and Support Vector Machines (SVM)
2.3 Random forest and decision tree models
2.4 Use of PCA, k-means clustering, and isolated forests for anomaly detection
2.5 Time-series prediction model and recommendation system
2.6 Selection, evaluation, and interpretation of models
Module 3 - Deep Learning using TensorFlow
3.1 Introduction to neural networking
3.2 Backpropagation
3.3 Stochastic gradient descent
3.4 Deep neural networking and its principles
3.5 CNNs, RNNs, LSTMs, and MLPs
3.6 GANs and Generative deep learning
3.7 Calculus and linear algebra
3.8 TensorFlow, CuPy, Keras, and PyTorch
Module 4 - Natural Language Processing
4.1 Natural Language Processing (NLP) and text mining
4.2 Data cleaning and preprocessing
4.3 Classification of text
4.4 Sentence structuring, language modeling, sequence tagging, and sequence tasks
4.5 Vector space models and semantics
4.6 Dialog systems
Module 5 - Image Processing and Computer Vision
5.1 Basics of computer vision and OpenCV
5.2 Use of neural networking for image processing
5.3 Classification and clustering of an image using GANs, multitask classifiers, and k-means
5.4 Detection of object
5.5 Image segmentation
5.6 Computer vision trends
Module 6 - Deployment of Machine Learning Systems to Production
6.1 Development of large-scale AI apps using various tools and techniques
6.2 Build and deploy APIs with FastAPI, Swagger, Paperspace, and Postman
6.3 CI/CD pipeline for model production
6.4 Use of TensorFlow Lite, TensorFlow.js, and Streamlit to package model
6.5 Model production using PyTorch, Spark, and PySpark
Module 7 - Work with Large Datasets
7.1 Data collection from RSSs, web scraping, and APIs
7.2 Data cleaning and transformation for ML systems
7.3 Automatic transformation tools
7.4 SQL and NoSQL databases to deal with large sets of data
7.5 Spark
7.6 Pandas
7.7 SQL and Spark SQL
7.8 ScrappingHub
Module 8 - Capstone Project
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.
Module 9 - Data Science with R
9.1 Introduction to R
9.2 R packages
9.3 Sorting DataFrame
9.4 Matrices and vectors
9.5 Reading data from external files
9.6 Generating plots
9.7 Analysis of Variance (ANOVA)
9.8 K-means clustering
9.9 Association rule mining
9.10 Regression in R
9.11 Analyzing relationship with regression
9.12 Advanced regression
9.13 Logistic Regression
9.14 Advanced Logistic Regression
9.15 Receiver Operating Characteristic (ROC)
9.16 Kolmogorov-Smirnov chart
9.17 Database connectivity with R
9.18 Integrating R with Hadoop
Module 10 - Git and GitHub
10.1 Introduction to Git
10.2 Architecture of Git
10.3 Working with remote repositories
10.4 Branching and merging
10.5 Git methodology
10.6 Git plugin with IDE (Eclipse)
The application is free and takes just 10-15 minutes to complete.
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
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, make new friends – the possibilities are endless and our community has something for everyone!
Career Oriented Sessions
Throughout the courseOver 20+ 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 completionGet 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 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.
1 on 1 Career Mentoring Sessions
After 90% of the course completionAttend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learners’ educational background, past experience, and future career aspirations.
3 Guaranteed Interviews
After 80% of the course completionGuaranteed 3 job interviews upon submission of projects and assignments. Get interviewed by our 400+ hiring partners.
Exclusive access to Intellipaat Job portal
After 80% of the course completionExclusive 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.
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
Tell us a bit about yourself and why you want to join this program
Application Review
An admission panel will shortlist candidates based on their application
Application Review
Selected candidates will be notified within 1–2 weeks
Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.
| Date | Time | Batch Type | |
|---|---|---|---|
| Program Induction | 26th Sep 2021 | 08:00 PM IST | Weekend (Sat-Sun) |
| Regular Classes | 26th Sep, 2021 | 08:00 PM IST | Weekend (Sat-Sun) |
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 will make you an expert and help you acquire all the necessary skills to land a high-income job at a reputed organization.
The trainers of this Machine Learning and Artificial Intelligence training program go through a rigorous selection process in order to give you the best trainers and learning experience in ML and AI.
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.
Once you complete the entire course, you will have the option to receive the status of an Executive Alumni after making a one-time payment of ₹5,000 as an alumni fee, which is not included in the course fee. However, this status is optional.
The entire course will be completed over the span of 9 months wherein you will learn all the courses and successfully complete the projects.
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