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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.
In collaboration with
Upskill for Your Dream Job
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.
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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:
Key Achievements of MNIT, Jaipur
Program in Collaboration with Microsoft
Benefits for students from Microsoft:
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
Decision Tree Models
Times-Series Prediction Model
With the best Ph.D. thesis (IIT Roorkee) and IEI Young Engineers awards, Dr. Nanda has a 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 more than 16 years of experience in cloud projects for Fortune 500 companies. He has a strong background in the architecture and implementation of AWS, Azure, GCP, along with hands-on experience in DevOps tools.
The application is free and takes only 5 minutes to complete.
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.
2.7 Python script
2.8 Python variable
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
4.1 Introduction to neural networking
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
5.1 Natural Language Processing (NLP) and text mining
5.2 Data cleaning and Preprocessing
5.3 Classification of text
5.4 Sentence structuring, language modeling, sequence tagging, and sequence tasks
5.5 Vector space models and semantics
5.6 Dialog systems
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
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
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
8.7 SQL and Spark SQL
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.
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
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)
The application is free and takes only 5 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
The project is included to provide learners with hands-on experience in financial data analysis. Analyze global sales numbers and profit data by developing an interactive map, and using map styles and layers for enhanced visualization.
The comprehensive project lets the learners use the ‘IF’ function to calculate the bonuses of all the employees at 10% of their salary and rate the sales employees as per the respective sales figures and rating scale.
As an important part of the project, learners will be required to analyze employment reliability in the telecom industry, and further work on real-time analysis of data with multiple labels, and data visualization for reliability factors.
The project involves using banking datasets to analyze, clean, process, and visualize the data. Once the data analysis is completed, the project also lets you learn to implement Naive Bayes and Principal Component Analysis.
The project requires learners to identify trends in the company’s inventory dataset to increase sales numbers. Moreover, they also need to implement data extraction, data manipulation, etc. for Market Basket Analysis.
In this project, you will work on a system that analyses user transactions and behavior. Based on this analysis, your system will identify parameters for unusual behavior in the system, such as incorrect passwords.
As an important requirement of this project, pre-process the data using tokenization and lemmatization. Also, perform a sentimental analysis task on the data by classifying whether movie reviews are positive or negative.
The project involves using banking datasets to analyze, clean, process, and visualize the data. Once the data analysis is completed, the project also lets you learn to implement Naive Bayes and principal component analysis.
This project allows you to implement data manipulation, data analysis, and data visualization to identify patterns in the Netflix dataset. It also assists you in learning to use several machine learning algorithms.
The project gives practical exposure to the applications of Python in web scraping. Also get a chance to work on various web scraping libraries, Beautiful Soup, Navigable String, parser, searching tree deployment, and more.
This project involves the analysis of naming trends using python. Also, use the python programming language to understand the applications of data manipulation, extract files with data, and concepts of data visualization.
Use Python 3.5(64-bit) with OpenCV for face detection. As an important requirement, learners need to ensure that the system will have to detect multiple faces in a single image. Working with essential libraries like cv2 and glob.
The candidates from Intellipaat were very good. They are better than experienced people from the same domain. The learners had hands-on experience. The product managers were very happy with the job-ready recruits.
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.
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
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.
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 opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)
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.
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!
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.
Tell us a bit about yourself and why you want to join this program
An admission panel will shortlist candidates based on their application
Selected candidates will be notified within 1–2 weeks
Total Admission Fee
Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.
|Program Induction||7th Oct 2023||08:00 PM IST||Weekend (Sat-Sun)|
|Regular Classes||7th Oct 2023||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 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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