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Our advanced Certificate program in Data Science and AI is designed to enhance your knowledge and understanding of data science and ML related concepts. Learn from MNIT faculty and industry specialists to master python, data wrangling, prediction algorithms, etc., through real-time projects and case studies.
In collaboration with
Learning Format
Online
Live Classes
12 Months
Career Services
by Intellipaat
Placement Assistance
Interviews
500+
Hiring Partners
This advanced certification in Data Science and AI led by MNIT, Jaipur faculty is curated to make you proficient in leading IT tools and technologies through industry-grade projects.
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 Post Graduate certificate program in Data Science and Machine Learning, you will:
Key Achievement of MNIT, Jaipur
Program in Collaboration with Microsoft
Benefits for students from Microsoft:
Understand the issues and create models based on the data gathered, and also manage a team of Data Scientists.
Build strategies on frameworks and technologies to develop AI solutions and help the organization prosper.
With the help of several Machine Learning tools and technologies, build statistical models with huge chunks of business data.
Design and build Machine Learning models to derive intelligence for the numerous services and products offered by the organization.
Create and manage pluggable service-based frameworks that are customized in order to import, cleanse, transform, and validate data.
Extract data from the respective sources to perform business analysis, and generate reports, dashboards, and metrics to monitor the company’s performance.
Skills to Master
Python
Data Science
Data Wrangling
SQL
Story Telling
Machine Learning
Prediction algorithms
Software Engineering
NLP
PySpark
Model
Data visualization
Tools to Master
A fellow of IETE and a senior member of IEEE, Vineet has published more than 100 research papers. He has guided 10 Ph.D. theses and many UG/PG dissertations. His research area includes trust, integrity, and resilience in hardware, pedagogy, etc.
A member of IEEE and reviewer of many journals, his research area includes MEMS and nano electronic devices, materials for sensors and actuators, with seven projects in the same. He has over 80+ published articles and two awards, one by DeitY.
He comes with more than 16 years of experience and worked with top MNCs like Apple, Amazon, etc.
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.
As 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, big data, and Pentaho projects.
Nishkam Shivam is a senior data scientist in analytics and AI at Bristlecone. He has more than nine years of experience in this field and has also worked in renowned companies like Accenture, Walmart, Emeritus, and many more.
Read More
Phaneendra Akula is currently working at Sunrise Biztech Systems Private Limited. He has more than nine years of experience in data science and has worked in prestigious companies like Genpact, TCS, and Tesco.
Vishwath Parthasarathy is a data scientist-III at InMobi. He has also worked at Amazon and PipeCandy. His expertise extends to machine learning, deep learning, MLOps, and algorithmic trading. He has been working as a data scientist since 2017.
Anurag Singh works at Schneider Electric Hub as a principal AI architect. He started as a software engineer in 2007 and has been working as a data scientist since 2018. He specializes in big data, data science, machine learning, and AI system architecture.
PythonÂ
Linux
To master AI, it is significant to familiarize yourself with Git, GitHub, and their various concepts and methods. This module will help you with exactly that.
2.1 Introduction to Git
2.2 Architecture of Git
2.3 Working with remote repositories
2.4 Branching and merging
2.5 Git methodology
2.6 Git plugin with IDE (Eclipse)
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.
3.1 PySpark
3.2 Python
3.3 NumPy
3.4 SciPy
3.5 Matplotlib
3.6 Pandas
3.7 Python script
3.8 Python variables
SQL Basics –Â
Advanced SQL – Â
Deep Dive into User-Defined Functions
SQL Optimization and Performance
As a data scientist, it is important to know how to design and build algorithms and analyze data. However, it is also important to explain that data in a story-like manner so that the members of the organization can understand the data and what information you have gathered from the same. This module will help you learn exactly that.
5.1 Practice data science concepts by building a story from data set
5.2 Develop questions that can be answered by the data set
5.3 Gain insights into the data using various plotting techniques and build a story
Machine learning is one of the core technologies involved in the field of artificial intelligence, apart from deep learning, neural networking, etc. This machine learning module will help you gain in-depth knowledge of the various theorems and techniques that play a significant role in the field of ML.
6.1 Regression Modeling: Logical and Linear
6.2 Classification Modeling: K-nearest neighbor, Naïve Bayes Theorem, and Support Vector Machines (SVM)
6.3 Random forest and decision tree models
6.4 Use of PCA, k-means clustering, and isolated forests for anomaly detection
6.5 Time-series prediction model and recommendation system
6.6 Selection, evaluation, and interpretation of models
In this module, you will master all the significant modules, concepts, and technologies to help you gain expertise in the field of machine learning. Also, you will learn in detail about the various prediction algorithms that are part of this technology.
7.1 Linear regression techniques
7.2Logistic regression techniques
7.3 Supervised learning
7.4 Unsupervised learning
7.5 Ensemble techniques
You have gained knowledge of the basic modules in machine learning and its various techniques. In this module, you will master the advanced-level techniques in this domain to prepare you for real-world scenarios.
8.1 Text mining
8.2 Social networking analysis
8.3 Recommendation systems
8.4 Time-series analysis
Apart from designing algorithms and crunching data, data science and machine learning experts are also required to write code and build software. In this module, you will learn to write the software code which will help you master the development of software prototypes and make them production-ready.
9.1 Coding
9.2 Testing
9.3 Debugging
9.4 Working with production systems
In this data science with PySpark module, our experts will teach you the numerous techniques involved data science using PySpark.
10.1 What is PySpark?
10.2 Need of Spark with Python
10.3 Fundamentals of PySpark
10.4 Advantages of PySpark over MapReduce
10.5 Use of PySpark in Data Science and Machine Learning
This module will make you proficient in working with TensorFlow and Keras, among the other tools and methods that are involved AI, deep learning, and neural networking.
11.1 Introduction to Deep Learning and Neural Networks
11.2 Multi-layered Neural Networks
11.3 Artificial Neural Networks and Various Methods
11.4 Deep Learning Libraries
11.5 Keras API
11.6 TFLearn API for TensorFlow
11.7 DNNS (deep neural networks)
11.8 CNNS (convolutional neural networks)
11.9 RNNS(recurrent neural networks)
11.10 GPU in Deep Learning
11.11 Autoencoders and restricted boltzmann machine (rbm)
11.12 Deep Learning applications
11.13 Chatbots
Natural Language Processing (NLP) and deep learning are a significant part of machine learning and artificial intelligence. This module will cover the various concepts and applications of deep learning and NLP.
12.1 Applications of NLP
12.2 Deep learning fundamentals
This module on computer vision and image processing will help you learn the basic and advanced level concepts and techniques that are required in artificial intelligence.
13.1 Basics of computer vision and OpenCV
13.2 Use of neural networking for image processing
13.3 Classification and clustering of an image using GANs, multitask classifiers, and k-means
13.4 Detection of object
13.5 Image segmentation
13.6 Computer vision trends
14.1 Why and when do we need MLOps?
14.2 AI pipelines
14.3 Training, tuning, and serving on the AI platform
14.4 Kubeflow pipelines on the AI platform
14.5 CI/CD for Kubeflow pipelines
As a data science and AI professional, a large part of your job involves dealing with large volumes of datasets. Here, you will learn to do so using various Python libraries, Spark, and other tools.
15.1 Data collection from RSSs, web scraping, and APIs
15.2 Data cleaning and transformation for ML systems
15.3 Automatic transformation tools
15.4 SQL and NoSQL databases to deal with large sets of data
15.5 Spark
15.6 Pandas
15.7 SQL and Spark SQL
15.8 ScrappingHub
Power BI Basics
DAX
Data Visualization with Analytics
Case Study:
This case study will cover the following concepts:
After completion of the Advanced Certification program in Data Science and Machine Learning, you will work on a real-time capstone project which will help you implement and validate the various concepts and skills that you have learned in the training.
Apart from python, you must also be familiar with R programming to build a successful career in data science. This data science with R module covers the various techniques and concepts in R which play a vital role in data science.
18.1 Introduction to R
18.2 R packages
18.3 Sorting DataFrame
18.4 Matrices and vectors
18.5 Reading data from external files
18.6 Generating plots
18.7 Analysis of Variance (ANOVA)
18.8 K-means clustering
18.9 Association rule mining
18.10 Regression in R
18.11 Analyzing relationship with regression
18.12 Advanced regression
18.13 Logistic Regression
18.14 Advanced Logistic Regression
18.15 Receiver Operating Characteristic (ROC)
18.16 Kolmogorov-Smirnov chart
18.17 Database connectivity with R
18.18 Integrating R with Hadoop
Projects will be a part of your Certification in Data Science and AI to consolidate your learning. It will ensure that you have real-world experience in data science and AI.
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
Admission
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.
| Date | Time | Batch Type | |
|---|---|---|---|
| Program Induction | 23rd Feb 2025 | 08:00 PM IST | Weekend (Sat-Sun) |
| Regular Classes | 23rd Feb 2025 | 08:00 PM IST | Weekend (Sat-Sun) |
This Post Graduate Program in Data Science and Machine Learning is led by top professionals from MNIT and experts in the field. Their main goal is to make you proficient in the various concepts, skills, and techniques involved in the respective field and keep you on track with the latest market demands and technological advancements.
After completion of this Post Graduate program, you will receive a completion certificate from the E&ICT Academy, MNIT Jaipur. Moreover, you will be awarded an industry-recognized Post Graduate Certificate in Data Science and Machine Learning from Microsoft.
Intellipaat provides career services that include Guarantee interviews for all the learners enrolled in this course. EICT MNIT Jaipur is not responsible for the career services.
The trainers of the PG certification in Data Science and ML program are top professors from MNIT and experts from top industries across the world. They are selected after going through a rigorous process where their skills, knowledge, and teaching ability are tested so that we can provide you with the best training experience.
This is a completely online PG program in Data Science and Machine Learning conducted by our experienced trainers from MNIT, Jaipur.
In case you fail to attend one or more live lectures, you will receive the recording of the session within the next 12 hours. Besides, if you require any other assistance, you will have access to our 24/7 online assistance platform.
Once you complete the program, execute the projects, and meet all the requirements, you will receive a joint Post Graduate certification from E&ICT and MNIT, Jaipur, along with certifications from Microsoft.
After completing the Post Graduate Program, you will be eligible to go through several mock interview sessions to prepare for your job interview, along with resume preparation. Moreover, you will get at least three interviews scheduled from our 200+ global hiring partners.
To get 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.
Yes, Intellipaat certification is highly recognized in the industry. Our alumni work in more than 10,000 corporations and startups, which is a testament that our programs are industry-aligned and well-recognized. Additionally, the Intellipaat program is in partnership with the National Skill Development Corporation (NSDC), which further validates its credibility. Learners will get an NSDC certificate along with Intellipaat certificate for the programs they enroll in.
What is included in this course?
