Our course is designed to enhance your knowledge and understanding of two of the most sought-after career fields, Data Science and Machine Learning. Here, you will gain expert knowledge of Python, data wrangling, prediction algorithms, etc., through live classes conducted by MNIT faculty and industry specialists and by implementing this knowledge in real-life projects.
In collaboration with
Upskill for Your Dream Job
202 Hrs Live Classes
This online Data Science and Machine Learning training program is curated by experts to make you proficient in leading tools and technologies in these IT sectors through industry-grade projects.
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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 lay an emphasis on bridging the gap between industry demand and academic approach to learning and provide 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:
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.
Mani has 16+ years of experience in working on cloud projects for fortune 500+ companies. He comes with strong architectural and implementation experience on AWS, Azure, GCP, along with DevOps tools.
A Senior Software Architect at NextGen Healthcare who has previously worked with IBM Corporation, Suresh Paritala has worked on Big Data, Data Science, Advanced Analytics, Internet of Things and Azure, along withRead More..
Module 1 - Preparatory Classes on Python for AI & ML and Linux
In this module, you will master the Python concepts and skills required to excel in AI & ML. This includes Python libraries, such as NumPy, SciPy, Matplotlib, etc., along with the fundamentals of the Linux operating system.
Module 2 - Git and GitHub
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)
Module 3 - Python with Data Science
In this module, you will get acquainted with the various libraries and functions in Python to help you understand the Data Science and Machine Learning concepts better.
3.7 Python script
3.8 Python variables
Module 4 - Data Wrangling with SQL
SQL is the most important skill required by Data Scientists or Data Engineers. You will learn in detail about the process of data collection, data wrangling, and data cleaning with the help of SQL.
4.1 Collect raw data and clean it
4.2 Use SQL to perform data wrangling
4.3 Relational and non-relational databases
4.4 Use of APIs to gather data
Module 5 - Story Telling
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
Module 6 - Machine Learning Models for Selection and Tuning
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
Module 7 - Machine Learning & Prediction Algorithms
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
Module 8 - Advanced Machine Learning
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
Module 9 - Software Engineering for Data Science
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.
9.4 Working with production systems
Module 10 - Data Science at Scale with PySpark
In this Data Science with PySpark module, our experts will teach you the numerous techniques involved in the field of 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
Module 11 - Artificial Intelligence and Deep Learning with TensorFlow
This module will make you proficient in working with TensorFlow and Keras, among the other tools and methods that are involved in the field of 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
Module 12 - Natural Language Processing
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
Module 13 - Image Processing and Computer Vision
This module on computer vision and image processing will help you learn the basic and advanced level concepts and techniques that are required in these areas of 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
Module 14 - Deployment of Machine Learning Systems to Production
There are various tools in AI that you need to excel in in order to master this technology. This module will cover some of the most popular and important tools in this IT field.
14.1 Development of large-scale AI apps using various tools and techniques
14.2 Build and deploy APIs with FastAPI, Swagger, Paperspace, and Postman
14.3 CI/CD pipeline for model production
14.4 Use of TensorFlow Lite, TensorFlow.js, and Streamlit to package model
14.5 Model production using PyTorch, Spark, and PySpark
Module 15 - Work with Large Datasets
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
15.7 SQL and Spark SQL
Module 16 - Data Visualization with Tableau
Data visualization plays a significant role in Data Science and Machine Learning. This module will help you become an expert in visualizing data with the help of one of the most popular and in-demand data visualization tools, Tableau.
16.1 Data visualization and Tableau
16.2 Tableau architecture
16.3 Graphs and charts
16.4 Data blending and metadata
16.5 Advanced data manipulations
16.7 Data organization and visual analytics
16.9 Expressions, calculations, and parameters
16.10 Dashboards and stories
16.11 Implementing R in Tableau
Module 17 - Capstone Project
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.
Module 18 - Data Science with R
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
The application is free and takes just 10-15 minutes to complete.
Projects will be a part of your PG Certification in Data Science and Machine Learning to consolidate your learning. It will ensure that you have real-world experience in Data Science and ML.
Working With NumPy
Work with the NumPy library to solve various Python problems. Create 2D arrays and perform simple arithmetic operations on two arrays.
Analyze COVID-19 Trends Using Python
Use Pandas to collect data from various files, Plotly to build interactive visualizations, and Prophet library from Facebook to develop time-series models.
Movie Recommendation System
Deploy Apache Spark, work with Spark MLLib, and perform regression, clustering, dimensionality reduction, and collaborative filtering to build a movie recommendation system.
Tweet Analysis with Twitter API Integration
Analyze tweets by integrating Twitter API. Use any one of the scripting languages, including Python, PHP, or Ruby to request for the API and receive the output in JSONRead More..
Facebook Dataset Analysis of a Cosmetic Brand
You will have access to the statistical data sets of the brand’s Facebook page and you will be required to use numerous techniques and methods to perform the requiredRead More..
Analysis on Customer Churn Dataset
Use Data Science and data visualization to perform real-time analysis on the reliability of the employees of the Telecom industry.
Use Python to perform web scraping. Also, work on various Web Scraping libraries, Beautiful Soup, Navigable String, parser, searching tree deployment, and more.
Conducting this case study will help you understand the structure of a dataset (PIMA Indians Diabetes database) and create a decision tree model based on it by making useRead More..
Insurance Cost Prediction
In this case study, you will understand the structure of a medical insurance dataset, implement both simple and multiple linear regressions, and predict values for the insurance cost.
This case study involves data analysis, column extraction from the dataset, data visualization, using the elbow method to find out the appropriate number of groups or clusters for theRead More..
Visualizing and Analyzing the Customer Churn dataset using Python
Analyze data by building aesthetic graphs to make better sense of it. Work with the bar plots and their applications, histogram graphs for data analysis, and box plots andRead More..
Analyzing the Naming Trends Using Python
Use Python programming to understand the applications of data manipulation, extract files with data, and concepts of data visualization.
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 SessionsThroughout the course
Over 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 BuildingAfter 70% of course completion
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 profile shortlisting stage
Mock Interview PreparationAfter 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 SessionsAfter 90% of the course completion
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 learners’ educational background, past experience, and future career aspirations.
3 Guaranteed InterviewsAfter 80% of the course completion
Guaranteed 3 job interviews upon submission of projects and assignments. Get interviewed by our 400+ hiring partners.
Exclusive access to Intellipaat Job portalAfter 80% of the course completion
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.
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
Get a chance to win a early bird discount of up to $ 88/-
Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.
|Program Induction||31st July, 2021||08:00 PM IST||Weekend (Sat-Sun)|
|Regular Classes||14th Aug, 2021||08:00 PM IST||Weekend (Sat-Sun)|
This online PG certification program in Machine Learning and Data Science 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 field of Data Science and Machine Learning and keep you on track with the latest market demands and technology advancements.
After the course, you will receive a course completion certificate from E&ICT Academy, MNIT Jaipur. Moreover, you will be awarded an industry-recognized certificate from IBM and Microsoft.
The trainers of the PG certification in Data Science and ML course 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 completely an online course 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 course, execute the projects, and meet all the requirements, you will receive a joint PG certification from E&ICT and MNIT, Jaipur, along with certifications from IBM and Microsoft.
After completing the course, you will have the eligibility to go through several mock interview sessions to prepare for your job interview, along with resume preparation. Moreover, you will get at least 3 interviews scheduled from our 200+ global hiring partners.
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