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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery	Frequency Of Classes
English	Self Study, Virtual Classroom	Video and Text Based	Weekends

Course Overview

The Post Graduate Certificate Program in Data Science and Machine Learning by Malaviya National Institute of Technology Jaipur offers learning opportunities to all enrolled candidates interested in pursuing careers in data science and machine learning. The institution is ranked 35th in NIRF rankings. The certification is in collaboration with IBM and Microsoft. The duration of the course is twelve months. Candidates will learn through the experienced faculty. The course curriculum is designed by faculties to provide required skills and techniques in the field.

Additionally, the Post Graduate Certificate Program in Data Science and Machine Learning is suitable for working professionals. They can study in this course if they want to upgrade their skills in the field. Participants, after completing this course, will receive a professional certification. Students can expect a hike in salaries and an increase in job opportunities after finishing this course.

The Highlights

Certification available
In collaboration with IBM and Microsoft
The duration of the course is twelve months
Offered by E and ICT MNIT Jaipur
Alumni status
Placement opportunity available
Early bird discount available
Online learning
154 hours of self-paced videos

Important dates

Other

Start Date : 23 Feb, 2025

Other

Start Date : 23 Feb, 2025

Other

Start Date : 23 Feb, 2025

Programme Offerings

Modules
Projects
live sessions
online learning.

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	MNIT JaipurIBMMicrosoft Corporation

The fees for the course Post Graduate Certificate Program in Data Science and Machine Learning is -

Head	Amount in INR
Total Admission Fee	₹ 1,12,005 (Inclusive of All)
EMI Starts at	₹ 4,999

Eligibility Criteria

Education

Students interested in Post Graduate Certificate Program in Data Science and Machine Learning should have an undergraduate degree with at least 50 per cent marks.

Certification qualifying details

After completing the course contents such as modules, projects candidates will get certification for the Post Graduate Certificate Program in Data Science and Machine Learning training course.

What you will learn

Machine learningData science knowledge

Candidates interested to pursue Post Graduate Certificate Program in Data Science and Machine Learning can gain knowledge through the following learning outcomes:

Candidates will learn about natural language processing
Students can gain knowledge through data science at scale with PySpark
Through the PG certification in Data Science and Machine Learning course, candidates will learn through the data visualisation with Tableau
The course offers the understanding of data science with R
Students will learn about artificial intelligence and deep learning with the tensor flow.

Who it is for

Data ScientistMachine Learning EngineerIT Engineer

Post Graduate Certificate Program in Data Science and Machine Learning will be helpful for the following candidates-

IT professionals looking for a career transition as Data Scientists and ML Engineers
Machine Learning and Business Intelligence professionals
Freshers aspiring to build a career in ML and Data Science field

Admission Details

Students interested in Post Graduate Certificate Program in Data Science and Machine Learning training course

can follow the details given below:

Step 1: Click on the URL, https://intellipaat.com/data-science-ai-mnit/

Step 2: Fill the application form.

Step 3: Get interviewed by our panel.

Step 4: Acquire an offer letter after getting shortlisted.

Application Details

Participants interested in Post Graduate Certificate Program in Data Science and Machine Learning online course should provide their name, qualifications, address, etc. for future reference.

The Syllabus

Python

Introduction to Python and IDEs
Python Basics
Object Oriented Programming
Hands-on Sessions And Assignments for Practice

Linux

Introduction to Linux
Linux Basics
Hands-on Sessions And Assignments for Practice

Introduction to Git
Architecture of Git
Working with remote repositories
Branching and merging
Git methodology
Git plugin with IDE (Eclipse)

PySpark
Python
NumPy
SciPy
Matplotlib
Pandas
Python script
Python variables

SQL Basics

Fundamentals of Structured Query Language
SQL Tables, Joins, Variables

Advanced SQL

SQL Functions, Subqueries, Rules, Views
Nested Queries, string functions, pattern matching
Mathematical functions, Date-time functions, etc.

Deep Dive into User Defined Functions

Types of UDFs, Inline table value, multi-statement table.
Stored procedures, rank function, triggers, etc.

SQL Optimization and Performance

Record grouping, searching, sorting, etc.
Clustered indexes, common table expressions.

Practice Data Science concepts by building a story from data set
Develop questions that can be answered by the data set
Gain insights into the data using various plotting techniques and build a story

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

Linear regression techniques
Logistic regression techniques
Supervised learning
Unsupervised learning
Ensemble techniques

Text mining
Social networking analysis
Recommendation systems
Time-series analysis

Coding
Testing
Debugging
Working with production systems

What is PySpark?
Need of Spark with Python
Fundamentals of PySpark
Advantages of PySpark over MapReduce
Use of PySpark in Data Science and Machine Learning

Introduction to Deep Learning and Neural Networks
Multi-layered Neural Networks
Artificial Neural Networks and Various Methods
Deep Learning Libraries
Keras API
TFLearn API for TensorFlow
Dnns (deep neural networks)
Cnns (convolutional neural networks)
Rnns (recurrent neural networks)
Gpu in Deep Learning
Autoencoders and restricted boltzmann machine (rbm)
Deep Learning applications
Chatbots

Applications of NLP
Deep learning fundamentals

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

Why and when we need MLOps
AI pipelines
Training, tuning, and serving on AI platform
Kubeflow pipelines on AI platform
CI/CD for Kubeflow pipelines

Data collection from RSSs, web scraping, and APIs
Data cleaning and transformation for ML systems
Automatic transformation tools
SQL and NoSQL databases to deal with large sets of data
Spark
Pandas
SQL and Spark SQL
ScrappingHub

Power BI Basics

Introduction to PowerBI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI.
SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI.

DAX

Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics

Slicers, filters, Drill Down Reports
Power BI Query, Q & A and Data Insights
Power BI Settings, Administration and Direct Connectivity
Embedded Power BI API and Power BI Mobile
Power BI Advance and Power BI Premium

Case Study

Creating a dashboard to depict actionable insights in sales data.

Introduction to R
R packages
Sorting DataFrame
Matrices and vectors
Reading data from external files
Generating plots
Analysis of Variance (ANOVA)
K-means clustering
Association rule mining
Regression in R
Analyzing relationship with regression
Advanced regression
Logistic Regression
Advanced Logistic Regression
Receiver Operating Characteristic (ROC)
Kolmogorov-Smirnov chart
Database connectivity with R
Integrating R with Hadoop

Evaluation process

Candidates interested in Post Graduate Certificate Program in Data Science and Machine Learning online course will receive certification after completing the course projects, modules and other contents.