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Data Science Course

5 (591 Ratings)

Learn Data Science from IIT Madras faculty & Industry experts and earn a Data Science certification from India's best Engineering College. Become a Data Scientist through multiple Data Science courses covered in this 7-month data science certification program with hands-on exercises & Project work. Master skills like Python, SQL, Machine Learning, Artificial Intelligence, PowerBI and more.

Ranked #1 Data Science Program by India TV

Data Scientist Course Key Highlights

50+ Live sessions across seven months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Madras Faculty & Industry Practitioners
1:1 with Industry Mentors
3 Guaranteed Interviews by Intellipaat
24*7 Support
No Cost EMI Option

Data Science Course Overview

What courses will this Data Scientist Program offer?

In this advanced certification program, you will learn 12 data science courses along with multiple case studies and project work.

Online Instructor-led:

  • Course 1: Fundamentals of Python & Linux
  • Course 2: Git
  • Course 3: Python for Data Science
  • Course 4: Advanced Statistics
  • Course 5: Machine Learning & Prediction Algorithms
  • Course 6: Data Science with PySpark
  • Course 7: AI and Deep Learning through Tensorflow
  • Course 8: MLOps
  • Course 9: Data Visualization using Tableau

Apart from the live classes, you will have electives in a self-paced format:

Data Analysis with Excel, Data Wrangling with SQL, NLP, and its applications.

The demand for Data Scientists exceeding the supply is a severe problem in the data-driven world we are living in today. As a result, most organizations are willing to pay high salaries for professionals with appropriate Data Science skills.

Data Science training online will help you become proficient in Data Science, R programming language, Data Analysis, Big Data, and more. Thus, you can quickly accelerate your career in this evolving domain and take it to the next level.

  • The average annual salary of Data Scientists as per Indeed is US$122,801 in the United States.
  • Data Scientist is the best job in the 21st century — Harvard Business Review
  • The number of jobs for all data professionals in the United States will increase to 2.7 million — IBM
  • Global Big Data market achieves US$122 billion in sales in 6 years — Frost & Sullivan

Advantages of Data Science

In the United States, the average salary of a Data Scientist is US$112,957. The average salary of Data Scientists in India is ₹853,191.

  1. Understand the Problem: Data Scientists should be aware of the business pain points and ask the right questions.
  2. Collect Data: They need to collect enough data to understand the problem at hand, and better solve it in terms of time, money, and resources.
  3. Process the Raw Data: We rarely use data in its original form, and it must be processed, and there are several ways to convert it into a usable format.
  4. Explore the Data: After processing data and converting it into a usable form, Data Scientists must examine it to determine the characteristics and find evident trends, correlations, and more.
  5. Analyze the Data: To understand the data, they use various tool libraries, such as Machine Learning, statistics and probability, linear and logistic regression, 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.
Criteria Data Analyst Business Analyst Data Scientist
Skillset Analyzing business needs Analyzing historical data Making data-driven decisions
Who are eligible? Anybody can learn Anybody can learn Anybody can learn
What do they do? Full life cycle analysis, including business needs, activities, and designing Implementing technology solutions and analyzing and reporting business capabilities Statistical analysis and the development of Machine Learning systems
Average salaries US$68,465 US$75,218 US$112,957
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With data collection, ’the sooner, the better’ is the best answer - The CEO of Yahoo
Everything is going to be connected with data and mediated by software - The CEO of Microsoft
The world is now awash in data, and we can see consumers more cleanly - The Co-founder of PayPal

Career Transition

55% Average Salary Hike

$1,20,000 The Highest Salary

12000+ Career Transitions

500+ Hiring Partners

Career Transition Handbook

Meet Your Mentors

Who can apply for the Data Scientist course?

  • Information Architects and Statisticians
  • Developers looking to master Machine Learning and Predictive Analytics
  • Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
  • Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
Who can aaply

What roles does a Data Scientist play?

Data Scientist

Design and implement scalable codes alongside effectively developing high-quality applications.

Analytics and Insights Analyst

Develop solutions for fixing quality issues in the data upon investigating the reported errors in the data.

AI & ML Engineer

Use Lambda functions and API Gateway to integrate Machine Learning models to web apps and deploy models in SageMaker.

Data Engineer & Data Analyst

Perform data cleansing, data transformation, analyze the outcomes and present the insights in reports and dashboards.

Junior Data Scientist

Analyze the operating behavior using advanced statistical techniques and tools. Also, create algorithms with prescriptive and descriptive methods.

Applied Scientist

Derive intelligence for the business products through designing and developing Machine Learning models.

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Skills Covered

Python

Data Science

Data Analysis

AI

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

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Tools Covered

tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop tool-desktop
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Data Science Course Fees

Online Classroom ( Intellipaat)

  • 50+ Live sessions across
  • 7 months of Instructor-led Training
  • One on One doubt resolution sessions

$999

Online Classroom Preferred

  • Live Classes from IIT Madras Faculty
  • Certification from CCE, IIT Madras
  • Job Assistance ( Mock Interviews, Resume Preparation)
  • Guaranteed 3 Interviews by Intellipaat
  • Dedicated Learning Manager
10 Dec

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08:00 PM TO 11:00 PM IST (GMT +5:30)

17 Dec

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

24 Dec

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

31 Dec

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,492 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Data Scientist Training Curriculum

Live Course Self Paced

Module 1 – Preparatory Session - Linux and Python

Preview

Python 

  • Introduction to Python and IDEs – The basics of the python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 

Module 2 – Data Analysis With MS-Excel

Preview

Excel Fundamentals 

  • Reading the Data, Referencing in formulas , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering 
  • Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security 
  • VBA Macros, Ranges and Worksheet in VBA 
  • IF conditions, loops, Debugging, etc.

Excel For Data Analytics 

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.  

Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Excel Power Tools 

  • Power Pivot, Power Query and Power View

Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve 
  • Multiple Classification Problems  

Information Measure in Excel

  • Probability, Entropy, Dependence 
  • Mutual Information 

Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions 
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression

Hands-on Exercise:

Classification problem using excel on sales data, and statistical tests on various samples from the population.

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.

Hands-on exercise: 

Writing comparison data between past year to present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

Extract Transform Load

  • Web Scraping, Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, dataframes, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.

Descriptive Statistics – 

  • Measure of central tendency, measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, bayes theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.

Introduction to Machine learning 

  • Supervised, Unsupervised learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.

Supervised Learning 

  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.

Unsupervised Learning 

  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.

Performance Metrics

  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.

Artificial Intelligence Basics 

  • Introduction to keras API and tensorflow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning 

  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 

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

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

Introduction to MLOps 

  • MLOps lifecycle
  • MLOps pipeline 
  • MLOps Components, Processes, etc

Deploying Machine Learning Models 

  • Introduction to Azure Machine Learning 
  • Deploying Machine Learning Models using Azure

Version Control 

  • What is version control, types, SVN.

GIT

  • Git Lifecycle, Common Git commands, Working with branches in Git
  • Github collaboration (pull request), Github Authentication (ssh and Http)
  • Merging branches, Resolving merge conflicts, Git workflow

The Data Science capstone project focuses on establishing a strong hold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals: 

  • Extracting, loading and transforming data into usable format to gather insights. 
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements. 
  • Model selection and model building on various classification, regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
  • Recommendation Engine – The case study will guide you through various processes and techniques in machine learning to build a recommendation engine that can be used for movie recommendations, restaurant recommendations, book recommendations, etc.
  • Rating Predictions – This text classification and sentiment analysis case study will guide you towards working with text data and building efficient machine learning models that can predict ratings, sentiments, etc.
  • Census – Using predictive modeling techniques on the census data, you will be able to create actionable insights for a given population and create machine learning models that will predict or classify various features like total population, user income, etc.
  • Housing – This real estate case study will guide you towards real world problems, where a culmination of multiple features will guide you towards creating a predictive model to predict housing prices.
  • Object Detection – A much more advanced yet simple case study that will guide you towards making a machine learning model that can detect objects in real time.
  • Stock Market Analysis – Using historical stock market data, you will learn about how feature engineering and feature selection can provide you some really helpful and actionable insights for specific stocks.
  • Banking Problem – A classification problem that predicts consumer behavior based on various features using machine learning models.
  • AI Chatbot – Using the NLTK python library, you will be able to apply machine learning algorithms and create an AI chatbot.

Text Mining, Cleaning, and Pre-processing

  • Various Tokenizers, Tokenization, Frequency Distribution, Stemming, POS Tagging, Lemmatization, Bigrams, Trigrams & Ngrams, Lemmatization, Entity Recognition.

Text classification, NLTK, sentiment analysis, etc  

  • Overview of Machine Learning, Words, Term Frequency, Countvectorizer, Inverse Document Frequency, Text conversion, Confusion Matrix, Naive Bayes Classifier.

Sentence Structure, Sequence Tagging, Sequence Tasks, and Language Modeling

  • Language Modeling, Sequence Tagging, Sequence Tasks, Predicting Sequence of Tags, Syntax Trees, Context-Free Grammars, Chunking, Automatic Paraphrasing of Texts, Chinking.

AI Chatbots and Recommendations Engine 

  • Using the NLP concepts, build a recommendation engine and an AI chatbot assistant using AI. 

RBM and DBNs & Variational AutoEncoder

  • Introduction rbm and autoencoders
  • Deploying rbm for deep neural networks, using rbm for collaborative filtering
  • Autoencoders features and applications of autoencoders.

Object Detection using Convolutional Neural Net

  • Constructing a convolutional neural network using TensorFlow
  • Convolutional, dense, and pooling layers of CNNs
  • Filtering images based on user queries

Generating images with Neural Style and Working with Deep Generative Models

  • Automated conversation bots leveraging
  • Generative model, and the sequence to sequence model (lstm).

Distributed & Parallel Computing for Deep Learning Models

  • Parallel Training, Distributed vs Parallel Computing
  • Distributed computing in Tensorflow, Introduction to tf.distribute
  • Distributed training across multiple CPUs, Distributed Training
  • Distributed training across multiple GPUs, Federated Learning
  • Parallel computing in Tensorflow

Reinforcement Learning

  • Mapping the human mind with deep neural networks (dnns)
  • Several building blocks of artificial neural networks (anns)
  • The architecture of dnn and its building blocks
  • Reinforcement learning in dnn concepts, various parameters, layers, and optimization algorithms in dnn, and activation functions.

Deploying Deep Learning Models and Beyond

  • Understanding model Persistence, Saving and Serializing Models in Keras, Restoring and loading saved models
  • Introduction to Tensorflow Serving, Tensorflow Serving Rest, Deploying deep learning models with Docker & Kubernetes, Tensorflow Serving Docker, Tensorflow Deployment Flask.
  • Deploying deep learning models in Serverless Environments
  • Deploying Model to Sage Maker
  • Explain Tensorflow Lite Train and deploy a CNN model with TensorFlow

Introduction to Big Data And Spark

  • Apache spark framework, RDDs, Stopgaps in existing computing methodologies

RDDs 

  • RDD persistence, caching, General operations: Transformation, Actions, and Functions.
  • Concept of Key-Value pair in RDDs, Other pair, two pair RDDs
  • RDD Lineage, RDD Persistence, WordCount Program Using RDD Concepts
  • RDD Partitioning & How it Helps Achieve Parallelization

Advanced Concepts & Spark-Hive

  • Passing Functions to Spark, Spark SQL Architecture, SQLContext in Spark SQL
  • User-Defined Functions, Data Frames, Interoperating with RDDs
  • Loading Data through Different Sources, Performance Tuning
  • Spark-Hive Integration
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Data Science Projects

Peer Learning

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!

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Career Services

Career Services
Resume

Career Oriented Sessions

Throughout 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

Resume & LinkedIn Profile Building

After 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 the profile shortlisting stage

Resume

Mock Interview Preparation

After 80% of the course completion.

Students will go through several mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

Resume

1 on 1 Career Mentoring Sessions

After 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, experience, and future career aspirations.

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Assured Interviews

After 80% of the course completion

Assured Interviews upon submission of projects and assignments. Get interviewed by our 500+ hiring partners.

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Exclusive access to Intellipaat Job portal

After 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.

Data Science Certification

What should I do to unlock my Data Science certification?

You can unlock your certificate issued by us in three simple steps:

  1. Complete the Data Science online course along with the given assignments
  2. Work on several industry-based projects and execute the same successfully
  3. Pass the certification exam

The certification you receive from us is valid for your entire lifetime, and top organizations worldwide recognize it.

On completing this Data Science online course and passing the exam, you will receive our Data Science certificate online via our Learning Management System. You can download or share your certificate from this through either email or LinkedIn.

Yes. This Data Science online certification issued by Intellipaat & CCE, IIT Madras is well-recognized in the industry.

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Data Science Training FAQs

Why should I enroll in this Data Science certification course?

We offer the best Data Science courses online for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:

  • A personal mentor to track your progress
  • Immersive online instructor-led sessions conducted by SMEs
  • Extensive LMS, allowing you to view recorded sessions within 3 hours
  • Real-time exercises, assignments, and projects
  • 24/7 learning support
  • A large community of like-minded learners
  • Industry-recognized Intellipaat badge
  • Personalized job support

Through this training, you will master the following concepts:

  1. Data analysis, project life cycle, and Data Science in the real world
  2. Machine Learning algorithms
  3. Techniques of evaluation, experimentation, and project deployment
  4. Analysis segmentation using clustering and the method of prediction
  5. Python with Data Science
  6. Git, Storytelling
  7. Data Science at scale with PySpark, AI with TensorFlow
  8. Deploying Machine Learning models on Clouds (MLOps)
  9. Data visualization with Tableau
  10. Natural Language Processing and its applications
  11. Microsoft Excel for data analysis and data transformation
  12. Data Science projects, analytics, and recommender systems

Intellipaat offers courses on Data Science, Machine Learning, Artificial intelligence, Python, Python for Data Science, Data Analytics, Business Analytics.

If you are looking for free resources on Data Science, then read our blogs on Data Science Tutorials and Data Science Interview Questions.

Data Science is a branch of computer science that deals with a wide range of algorithms, tools, scientific methods, and Machine Learning techniques to identify hidden trends and patterns from structured and unstructured data.

Data Scientists are experts in Data Science responsible for collecting and analyzing vast chunks of structured and unstructured data from a range of data sources. These professionals combine their knowledge and skills in mathematics, statistics, and computer science to enable organizations to analyze and process business data and interpret it to help the company make improved business decisions.

There are several ways to become a Data Scientist. The Data Scientists use numerous Data Science tools/technologies, such as R and Python programming languages and SAS analysis tools. As a budding Data Scientist, you should be familiar with data analysis, statistical software packages, data visualization, and handling large datasets. Data Scientists spend the majority of their time in data exploration and data wrangling.

Python is the most popular and preferred language in Data Science because it is an easy-to-use, easy-to-learn, open-source programming language. Moreover, it is a dynamic language that supports multiple paradigms. Apart from this, some other languages used in Data Science include R and SQL.

Many top companies hire Data Scientists. A few of them are Amazon, Google, IBM, Facebook, Microsoft, Walmart, Target, Visa, Bank of America, Accenture, Fractal Analytics, etc.

There are numerous job opportunities available for Data Scientists, like:

  • Business Analyst
  • Data Analyst
  • Big Data Engineer
  • Data Scientist
  • Statistician
  • Data Engineer
  • Machine Learning Engineer
  • Data Architect

It does not take too long to become a Data Scientist. Once you complete the Data Science training with us, execute all the projects successfully, and meet all the requirements, you will receive an industry-recognized Data Science course completion certificate. Further, with the help of our placement team, who will prepare your resume and conduct mock interviews before your job interviews, you will be able to crack your interview and land a high-paying job as a Data Scientist.

This Data Science course is for beginners who are new to Data Science and experienced professionals who wish to upskill themselves in this domain.

You will gain access to our job portal once you complete the entire training program and execute the assignments and projects part of the program.

At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.

Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.

Apparently, no. Our job assistance program is aimed at helping you land in 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 decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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The Rise in Popularity and Demand for Data Science Courses

MarketsandMarkets analysis has predicted that the market size of the data science platform will reach USD 140.9 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 30% during the forecast period.

The demand for Data Science is primarily a result of businesses worldwide trying to remain competitive by increasingly using digital technologies. On the other hand, there is a huge demand for Data Scientists because there are not enough skilled professionals to fill the vacancies created by these businesses. This short supply, in turn, has made Data Science one of the highest-paying jobs in the world. Hence, Data Science aspirants are looking for the best Data Scientist courses.

The role of a Data Science professional is to essentially help businesses make informed decisions and solve critical problems through insights generated by interpreting and managing large, complex sets of data.

Intellipaat has collaborated with several top-rated institutions to bring you Data Science courses tailored for anyone who wishes to pursue this career. We have certification programs like Advanced Certification in Data Science and AI by CCE, IIT Madras, PG certification in Data Science and Machine Learning by MNIT, Jaipur, Masters in Data Science online program, Data Science online course, Big Data and Data Science Master’s course, and the MCA degree program with a specialization in Data Science by Jain University.

What is Data Science?

Data Science deals with a wide range of algorithms, scientific methods and tools, and Machine Learning techniques to identify hidden patterns and trends in data. It focuses on various aspects of data like quantitative synthesis and analysis of data to achieve business goals.

What are the benefits of Data Science?

Data Science empowers businesses to make better decisions by evaluating their performances based on trends and patterns, helping them specify goals and opportunities.

  • It helps adopt best practices and focus on genuine issues
  • It helps make sound decisions based on data-driven and quantifiable insights
  • It identifies and refines target audiences to increase conversion rates.

Why is Intellipaat the best choice for Data Science courses?

Intellipaat’s Data Science course has been ranked the number one Data Science Program by India TV. The Data Science course stands as the best choice for someone looking for a bit of flexibility. This online course offers live instructor-led sessions as well as self-paced learning. This course is very suitable for professionals who want to upskill without causing disruptions in their professional lives.

The course follows and maintains industry standards and provides a certification that top organizations and MNCs recognize well. After completing the course, our learners also get the opportunity to immediately apply for jobs with help from our career services team.

As long as you have a good internet connection and a computer, phone, or tablet, you will be able to study from anywhere in the world. So, enroll in the Data Science online course offered by Intellipaat and receive the proper guidance from experts who have years of experience in the industry.

FAQs

Is doing a Data Science course worth it?

Of course! Data Science as a career can be pretty rewarding due to the high demand for experts in this domain, sky-high salaries, and the value addition to businesses across various industries.

Is coding required to learn Data Science?

Sometimes. While it is not necessary to have advanced coding skills, it is good if learners are comfortable with data analytics, data management, and data visualization.

Fundamental knowledge in C/C++, Python, R, Java, or SQL can boost your learning process. Learning any of these programming languages would serve you in grouping the unstructured datasets.

What skills will help during the Data Science training?

It will be beneficial for you during the learning process if you have the following skills:

  • Mathematical Skills: Linear algebra, calculus, matrices, gradients, etc.
  • Programming Skills: Python, Java, SQL, C, C++, etc.
  • Data Processing: Data mining, data processing, data modeling, etc.
  • Statistical Analysis: Analytical tools like Hadoop, SAS, R, etc.
  • Data Visualization Skills: Matplottlib, Tableau, and several other data visualization tools

How to learn Data Science?

  • Who should learn Data Science?

If you have the passion and knack for Data Science, that is all that is required. You must be enthusiastic about the tools and techniques that are essential in this domain. If you are good at mathematics, statistics, any programming language, or any data visualization tool, you will quickly master the concepts.

  • How can I start learning Data Science and become a master in it?

The first thing to do is get familiar with all the concepts, applications, various tools, and techniques of Data Science. Consistency in learning and practice is the only way to stay updated and relevant in the Data Science world.

  • How do I learn Data Science online?

You can check out all the online Data Science courses that Intellipaat offers. You will also find various tutorials, blogs, interview guides, and community forums to aid your learning.

These courses will help working professionals master this technology without interrupting work hours. The curriculum of these online programs meets industry requirements and standards.

  • What are the best learning paths for Data Science?

All kinds of degrees and certifications related to Data Science is a good career path in Data Science as you will get the opportunity to gain proficiency in this technology. However, before finalizing, make sure to learn whether the program and faculty are suitable for your learning style.

It is better to opt for an online course if you are already working and want to learn while you earn.

  • How can I become a Data Scientist?

Learning about Data Science and its prerequisites are the first steps to start your journey as a future Data Scientist. The next step is to enroll yourself in one of the Data Science programs that any reliable and trustworthy institution offers. Last but not least, practice and keep yourself up-to-date with all the latest information on this technology.

Intellipaat’s Data Science Courses

  • What are some recommended data science courses by Intellipaat?

Intellipaat has collaborated with top-rated institutions to bring you several Data Science programs tailored to individuals and professionals who wish to become successful Data Scientists. Here are a few recommended courses that you may find is suitable for you:

  • Advanced Certification in Data Science and AI by CCE, IIT Madras
  • PG certification in Data Science and Machine Learning by MNIT, Jaipur
  • Masters in Data Science online program
  • Data Science online course
  • Big Data and Data Science Master’s course
  • MCA degree program with a specialization in Data Science by Jain University
  • Python for Data Science

You can always reach out to our course advisors if you are unsure which course is right for you.

  • Why choose the Data Science online course by Intellipaat?

In this course, you can learn Data Science from the faculty of IIT Madras and get certified by India’s #1 Engineering College. This 7-month certification program has a curriculum covering all Data Science concepts with hands-on exercises & project work that meet industry requirements.

  • Why choose the Advanced Certification in Data Science and AI by CCE, IIT Madras?

The faculty lead this Advanced Certification in Data Science and AI course at IIT Madras faculty. It is a 7-month certification program that aims to help you master all the basic and advanced-level concepts and tools essential in Data Science, Machine Learning, Deep Learning, and Artificial Intelligence.

  • Why choose the PG certification in Data Science and Machine Learning by MNIT, Jaipur?

The PG certification in Data Science and Machine Learning will enhance your knowledge and understanding of Data Science and Machine Learning. The live classes conducted by MNIT faculty extensively focus on Python, data wrangling, prediction algorithms, machine learning models, AI, deep learning, etc. The course is in collaboration with IBM and Microsoft, and at the end of the course, you will receive a PG certification from E&ICT Academy, MNIT.

  • Why choose the Masters in Data Science online program?

The master’s in Data Science online program lets you gain proficiency in Data Science with R, Hadoop, Apache Spark, Scala, Deep Learning, Tableau, Data Science with SAS, SQL, MongoDB, real-time analytics, and more. The course covers ten courses and 30 industry-based projects with 1 CAPSTONE project.

There are five additional self-paced courses co-created with IBM viz. R for Data Science, Deep Learning with TensorFlow, Build Chatbots with Watson Assistant, Spark MLlIb, and Python for Data Science. Learners will get exclusive access to IBM Watson Cloud Lab for Chatbots course.

  • Why choose the Big Data and Data Science Master’s course?

This master’s course covers 20 courses and 56 industry-based projects with in-depth knowledge of designing, developing, and deploying Data Science and Big Data applications in the real world. The course will help you become a Big Data and Data Science Architect. By the end of the course, you will become proficient in statistical computing, real-time analytics, parsing machine-generated data, creating NoSQL applications, deep Learning, Artificial Intelligence, etc.

  • Why choose the MCA degree program with a specialization in Data Science by Jain University?

This is a 2-year degree program that includes basic, foundational, and advanced courses in MCA from the experts at Jain University. Additionally, you can choose Data Science as a specialization course. Seasoned industry experts teach the course at Intellipaat. The MCA degree is by Jain University, and Intellipaat will give the PG certification once the course ends. You will also receive career services from Intellipaat with three guaranteed Interviews from top MNCs.

  • Why choose the Python Data Science Certification Course by Intellipaat?

This Python for Data Science certification course will help you master Data Science using Python. Once enrolled, you will get the opportunity to work on various Python libraries such as SciPy, NumPy, Lambda function, Matplotlib, etc., and master Data Science Analytics skills through real-world projects.

Why Intellipaat?

  • Who would be teaching these courses?

You will be learning from the best. The faculty of Intellipaat are experts in their domain and have over 12 years of experience. The trainers emphasize 1:1 mentoring to ensure that each learner is confident in their Data Science skills and knowledge.

  • What is unique about the curriculum?

In addition to the learners learning under the expert guidance of Intellipaat faculty, the course focuses on helping them train from real industrial scenarios. The corporate partners of this program are some top-rated institutions that include real-world practitioners of Data Science. They are strongly involved in curriculum design, industry lectures, facilitating projects, and performing professional evaluations.

  • Will Intellipaat assist in selecting the best-suitable Data Science course?

Our course advisors are here to do just that. They help prospective learners pick the best course suitable for them and tailor it according to their convenience. Make sure to reach out to our course advisors for more information.

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