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iHUB IIT R

Data Science Course

96,569 Ratings

Rated #1 Data Science Course by India TV

  • Master Data Science courses: Python, SQL, ML, Power BI, NLP, Gen AI, & more
  • Live online Interactive sessions from IIT faculty & top industry experts
  • Guaranteed placement support with our career services
  • Earn prestigious data science certification from iHub DivyaSampark IIT Roorkee & Microsoft
In Collaboration With
Microsoft
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Key Highlights

50+ Live interactive sessions across 7 months
218 Hrs Self-paced Videos
50+ Industry relevant Projects & Quizzes
Live Classes from IIT Faculty & Industry Experts
Certification from iHub IIT Roorkee & Microsoft
Career Services by Intellipaat
2 Days Campus Immersion at iHub IIT Roorkee
24/7 Support
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Trustpilot 3109
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About Data Science Course Overview

What courses will this Data Science Program offer?

In this advanced Data Science Certification program, you will undergo 10+ Data Science Courses along with multiple case studies and industry-oriented project work.

Online Instructor-led Interactive Sessions:

  • Course 1: Linux and Python Fundamentals
  • Course 2: Data Wrangling with SQL
  • Course 3: Python with Data Science
  • Course 4: Linear Algebra and Advanced Statistics
  • Course 5: Machine Learning and Prediction Algorithms
  • Course 6: Supervised and Unsupervised Learning in ML
  • Course 7: Deep Learning with Tensorflow
  • Course 8: Generative AI & Prompt Engineering
  • Course 9: Deploying Machine Learning Models on Cloud
  • Course 10: Data Visualization Tool Power BI

Additionally, Data Science Capstone Projects and multiple electives will be provided to enhance your knowledge in the Data Science & AI domain with this data science course

In this data science course, you will master the key skills to become a successful data scientist, such as:

Linux: Learn basic Linux commands to gain expertise with Linux command line. Most of the production systems in the world runs on Linux.

Python For Data Science: Master practical skills with Python programming & its data science libraries like Pandas, Numpy, Matplotlib, etc. Get hands on with ETL (Extract, transform, Load) in this data science course.

Statistics: To become a successful data scientist, one needs to have decent knowledge of mathematics like linear algebra, & more.

Machine Learning: Master supervised and unsupervised algorithms with this program and solve business problems using algorithms.

Artificial Intelligence: Understand how neural network works, its implementation in the business. Work on projects & create your own AI applications.

Power BI: Master most widely used visualization tool by Microsoft. Learn how to create complex interactive dashboards and management reports.

MLOps: Once you have mastered the Machine Learning algorithms, it’s a time to deploy the machine learning model you have created on the cloud platform, like AWS or Azure.

MS Excel: Learn Excel analytics from scratch to master data transformation, data manipulation, data modelling and reporting.

Generative AI: Master prompt engineering and tools like ChatGPT to build data science application at lightning speed.

Data Scientists are in high demand and offered high-paying jobs. This allows for diverse career opportunities in data science, along with innovation and solving complex business problems. We live in an AI era where Data Scientists enjoy global job prospects and the ability to influence key decisions in the organization.

Some of the core responsibilities of data scientists are:

  1. Understand the Problem: Data scientists should be aware of the business-pain-points and ask the right questions.
  2. Collect Data: They collect enough data to understand the problem in a better manner.
  3. Process the Raw Data: We rarely use data in its original form, and it must be processed. There are several ways to convert it into a usable format.
  4. Explore the Data: After processing data and converting it in a usable form, data scientists must examine it to determine its characteristics and find evident trends, correlations, and more.
  5. Analyse the Data: To understand the data, they use various tool libraries, such as machine learning, statistics and probability, time series analysis, and more.
  6. Communicate Results: At last, results must be communicated to the right stakeholders, laying the groundwork for all identified issues.

Our data science certification course will help you to master data scientist skills in just 7 months.

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Data Science Career Transitions

55% Average Salary Hike

45 LPA The Highest Salary

12000+ Career Transitions

500+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Data Science Training Mentors

What role does a Data Scientist play?

Data Scientist

Design and implement scalable applications using AI & ML algorithms.

Data Analyst

Develop application for fixing data quality issues and get data insights.

AI & ML Engineer

Build LLM to build innovative applications for the future.

Data Engineer

Perform design, build and maintain the infrastructure to handle large volume of data and large-scale applications

Junior Data Scientist

Works on Data Analysis, Model building and data cleansing. Uncover data insights & solve business problems

Applied Scientist

Develop and deploy machine learning solutions to solve real world problems.

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28+ Skills Covered under this Data Scientist Course

Python Programming

SQL

Story Telling

Inferential Statistics

Machine Learning

Mathematical Modelling

Descriptive Statistics

Data Analysis

Generative AI

Prompt Engineering

ChatGPT

Artificial Intelligence

Large Learning Models

Supervised Learning

Unsupervised Learning

MLOps

Data Visualization

Conversational AI

Ensemble Learning

Exploratory Data Analysis

Data Science

Big Data

Data Mining

Statistical Learning

Research Methods

Hypothesis Testing

Statistical Analysis

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12+ Data Science Tools Covered

pyspark 1 python 2 jupyter 3 Scipy 2 numpy 2 pandas matplotlib tensorflow 1 SQL 1 Power BI excel 1 git

Fees

Online Classroom Preferred

  • Live Classes from IIT Faculty & Industry Experts
  • Earn data science certification from iHub IIT Roorkee,& Microsoft
  • Work on Industry Oriented Projects
  • Elevate your career with our placement support
Weekend (Sat-Sun)

14 Dec 2024 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

14 Dec 2024 10:00 AM - 01:00 PM
Weekday (Tue-Fri)

17 Dec 2024 07:00 AM - 09:00 AM
₹65,037 10% OFF Expires in

EMI Starts at

₹5,000

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs

Financing Partners

EMI Partner

The credit facility is provided by a third-party credit facility provider and any arrangement with such third party is outside Intellipaat’s purview.

Corporate Training

  • Customized Learning
  • Enterprise Grade Learning Management System (LMS)
  • 24x7 Support
  • Enterprise Grade Reporting

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Data Science Course Syllabus

Live Course Self-Paced Industry Expert Academic Faculty

Preparatory Session - Linux and Python

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Python

  • Learn the basics of Python, along with how to use them in IDEs
  • Deep dive into the fundamentals of OOPS concepts like Classes, Objects, Inheritance, etc.

Linux

  • Get started with the fundamentals of Linux
  • Learn the Linux Architecture, along with commonly used commands in Linux
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  • Understand the basics of SQL, such as creating tables, updating tables, etc.
  • Deep dive into SQL joins and learn about Left join, Right join, etc.
  • Know why SQL functions are needed and how to use them, along with using subqueries in SQL.
  • Learn SQL Nested Queries and understand User Defined Functions in SQL.
  • Learn how to do SQL Optimization and improve the performance of SQL queries.
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  • Understand how to use Python for Data Science and the importance of Python APIs. Learn how to create APIs with Python.
  • Deep-dive into the nitty-gritty of Data Manipulation and Data Handling in Python using NumPy and Pandas.
  • Know the importance of Data Preprocessing and Visualization and their Python implementation.
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  • Re-visit Linear Algebra and Advanced Statistics for machine learning.
  • Deep-dive into Descriptive Statistics, Inferential Statistics, and Probability.
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  • Introduction to machine learning, why it is essential, and how it works.
  • Understand regression, classification, and clustering algorithms. Also, learn when to use which algorithm.
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  • Understand what linear and logistic regression is and the difference between them.
  • Learn and implement Decision Tree and Random Forest algorithms, and understand when to use decision tree vs random forest.
  • Acquire hands-on skills in Support Vector Machine and Gradient Descent.
  • Learn what K-Nearest Neighbors and Time Series Forecasting is.
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  • Master the fundamentals of K-means clustering along with Dimensionality reduction. Learn linear discriminant analysis and principal component analysis.
  • Understand the importance and usage of Performance Metrics and Classification Reports.
  • Learn how to evaluate machine learning models using the Confusion matrix.
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  • Learn the basics of Artificial Intelligence and Deep Learning. Get a deeper understanding of neural networks and their different types.
  • Understand the internal workings of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), along with various real-time scenarios.
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  • Explore the fundamentals of LSTM and its advantages over RNN. Learn to make them suitable for complex time series data analysis and sequence-based tasks.
  • Deep-dive into the mechanics of Transformer architecture, learn how they have improved traditional NLP techniques, and why they are better at understanding context.
  • Learn what BERT is and how it can understand the deep contextual meaning of sentences. Learn its application in text classification, sentiment analysis, and question answering.
  • Understand GPT models and the importance of autoregressive learning. Learn how GPT models are trained on vast datasets and how to fine-tune them for different creative applications.
  • Learn the evolution of large language models (LLMs) and their architecture, to perform complex language understanding and generation tasks.
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  • Use ETL processes to make data usable, along with data manipulation and visualization techniques to gather insights and pre-process data.
  • Understand how to do Feature Engineering to enhance the performance of machine learning models. Learn to select the right supervised or unsupervised algorithm for varied use cases and problems.
  • Learn how to evaluate and monitor machine learning models.
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  • Recommendation Engine: Learn how to create recommendation engines using collaboration filtering and content-based methods. Then, render personalized recommendations using datasets from E-Commerce platforms and video streaming services.
  • Rating Predictions: Learn how to predict user ratings using machine learning models on various datasets such as movie ratings, product reviews, and customer satisfaction analysis.
  • Census: Analyse and interpret Census data using various machine-learning techniques. Learn to find patterns using multiple criteria, such as demographics, age, etc.
  • House Price Prediction: Learn to build a machine learning model in this certification course that can predict house prices by being trained on historical house prices.
  • Object Detection: Understand the fundamentals of object detection. Learn how to detect objects in images and videos.
  • Stock Market Analysis: Learn to analyze stock market data using time series analysis and learn how to build predictive models for stock prices and market trends.
  • Banking Problem: Learn to solve real-world banking problems using machine learning models. Work on problems such as fraud detection, credit risk assessment, and improved decision-making.
  • AI Chatbot: Work on creating powerful chatbots powered by AI. Learn how to design a conversational AI using Natural Language techniques.
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  • Learn to create compelling resumes and strategies for making your resume ATS compliant.
  • Understand how to create a job search strategy and align your LinkedIn with target job roles.
  • Take Mock Interviews with real-time hiring managers along with actionable feedback on how you can perform better.
  • Get access to our network of 3,100+ hiring partners and early access to applying for open job roles at these companies.
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Electives

  • Learn the basics of PowerBI, Data Modelling, and DAX. Then, implement Time Intelligence Functions and learn the advanced features of DAX.
  • Understand the use of Slicers, filters, and Drill-down Reports. Learn features such as Power BI Query, Q&A, and Data Insights.
  • Deep dive into Power BI Settings, Administration, and Direct Connectivity
  • Learn how to integrate PowerBI features into custom applications using the Embedded Power BI API. Then, explore the features of Power BI Mobile for accessing reports and dashboards.
  • Understand the advanced concepts of Power BI functionalities such as complex data modeling, DAX formulas, and report optimization.
  • Learn Power BI Premium and the extra features it offers.
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  • Learn the fundamentals of MLOps and the lifecycle of developing and deploying Machine Learning Models.
  • Get started with Azure machine learning service. Deploy your first machine learning model on Azure Machine Learning.
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  • Learn the importance of version control and the different types of tools that can help with version control.
  • Get introduced to Git and it’s lifecycle. Learn the standard Git commands.
  • Understand the concept of branching in git, why it is used, and how to create and use branches in git.
  • Connect your local git repository to GitHub, and learn how to authenticate to GitHub using SSH and HTTP.
  • Learn how to merge branches and how to resolve Merge Conflicts.
  • Understand how to work with big development teams and cross-team using Git workflows.
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  • Learn the fundamentals of Excel along with data analytics for Excel.
  • Understand the art of visualization using Excel properties along with Excel Power Tools.
  • Know how to solve classification and regression problems in Excel along with when and why to use them.
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Data Science Projects

Career Services

Career Services
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Placement Assistance
job portal
Exclusive access to Intellipaat Job portal
Mock Interview Preparation
One-on-One Career Mentoring Sessions
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Career Oriented Sessions
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Resume & LinkedIn Profile Building
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Data Science Certification

Advanced Certification in Data Science and AI Click to Zoom

About iHUB DivyaSampark, IIT Roorkee

iHUB DivyaSampark at IIT Roorkee is the Innovation Centre at IIT Roorkee, established under the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) by the Department of Science and Technology (DST). It focuses on fostering innovation in advanced technologies like AI, Machine Learning, Cloud Computing, and more. The hub plays a pivotal role in technology, incubation, and startups.

Key Achievement of IIT Roorkee:

You can unlock your Data science certification issued by us in two simple steps:

  1. Complete the given assignments and Quizzes
  2. Work on capstone project and submit them

Data Science Certification Course Reviews

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Data Science Training FAQs

What are the salary trends of Data Science professionals in India and the USA?

In India, Data Scientist’s salaries have been rising with entry-level positions getting ₹6,00,000 per year whereas experienced professionals earn up to ₹20,00,000 annually. In the USA, the average annual salary is approximately $156,790, with entry-level roles starting around $117,276 and experienced professionals earning up to $190,000.

This Data Science course is of 7 months and we expect you to put 8 hrs per week to attend the live sessions and complete assignments, case studies, and project work.

You will get the below-mentioned learning in our data science course.

  • A personal mentor to track your progress
  • Immersive online instructor-led sessions conducted by Industry Experts
  • Real-time exercises, assignments, and industry-oriented projects
  • 24/7 learning support
  • 1:1 doubt clearance by subject matter experts
  • Forum to interact with likeminded learners
  • Personalized job support & access to the job portal

Data scientists are responsible for collecting, processing, and analyzing data from different data sources. They create predictive models and interpret the data to gain meaningful insights. The data insights are communicated to business teams to make informed business decisions.

Python is the most popular and preferred language for building Data Science applications. It is an easy-to-use, easy-to-learn, and open-source programming language. Apart from this R and SQL are used by Data Scientists. In our Data Science course all these programming languages will be covered.

Here are the steps for getting into the placement pool:

  1. Complete the Data Science course and submit the mandatory assignments and projects within the given timelines.
  2. Clear the Placement Readiness Test (PRT)

Upon clearing the PRT learner will get access to the dedicated jobs from Intellipaat as well as the career mentoring sessions.

Yes, certainly this data science training course will help you land in data science jobs upon online course completion.

To become a data scientist, you need to have good mathematics & Python knowledge along with data visualization tools like Power BI. The knowledge of Machine Learning and AI algorithms with hands-on exposure is vital. Our online data science course will help you attain these required skills.

The decision between a Data Science course and a data analytics course depends on your goals. Data Science is broader and focuses on gaining insights, creating models, and solving complex problems using various techniques. Data Science is best suited for those interested in research, and innovation with a decent grasp of coding skills.

On the other hand, data analysis is more about interpreting existing data to make data-driven decisions. If you enjoy playing with data and contribute to business strategies, data analytics may be a better fit.

We provide 24/7 support to our learners for their Data Science doubt resolutions. You can get the required support using our dedicated chat support or directly raise the ticket from the LMS. You can also avail 1:1 session for doubt clearance with our Teaching Assistant (TA) team.

No, our job assistance is aimed at helping you land your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final hiring decision will always be based on your performance in the interview and the requirements of the recruiter.

Intellipaat provides a variety of options to study Data Science which include certification and a Master’s degree program. You can choose any of the programs as per your aspiring career goals. All the courses are taught by top faculty and Industry experts. For more details, you can visit these similar Data Science Courses:

Artificial Intelligence Course

Machine Learning Certification Course

Data Analytics Course with Placements

Business Analytics Course

Power BI Course

Yes, as per our refund policy, once the enrolment is done, no refund is applicable.

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