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Quick Facts

Medium Of InstructionsMode Of LearningMode Of DeliveryFrequency Of Classes
EnglishSelf Study, Virtual ClassroomVideo and Text BasedWeekends

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 
  • 202 hours of instructor-led training 
  • 154 hours of self-paced videos 
  • 404 hours of exercises and projects

Programme Offerings

  • Modules
  • Projects
  • live sessions
  • online learning

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesMNIT JaipurIBMMicrosoft Corporation

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

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/pg-certification-data-science-machine-learning-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.

Instructors

MNIT Jaipur Frequently Asked Questions (FAQ's)

1: What is the duration of Post Graduate Certificate Program in Data Science and Machine Learning programme?

The duration of the course is twelve months.

2: What is the mode of learning?

Candidates can learn through this course in online mode only.

3: How can I access the contents of the course?

Candidates can access the Post Graduate Certificate Program in Data Science and Machine Learning syllabus only after successful enrollment.

4: Is placement opportunity available after completing the course?

Placement assistance is provided by the platform of the Intellipaat job portal.

5: What if I need assistance?

Candidates will receive 24x7 assistance through the platform.

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