AI & Data Science Certification Course [Hindi]
This Data Science online course will show you how to turn big piles of data into amazing discoveries. You’ll learn to find hidden patterns, make smart predictions, and solve real problems. Whether you’re a student or a newbie professional, join us to unlock the secrets of data and shape the future!
What will you take home from TechVidvan Data Science Course?
- 100+ hrs self-paced Data Science course
- 200+ hrs of comprehensive study material
- 210+ hrs of real-world practicals
- 50+ Interactive quizzes & assessments
- 700+ Data Science Interview questions for top MNCs
- 70+ Real-time projects with implementation
- 120+ Data Science Practical Code Examples
- 98% Positive reviews from learners
- 85+ Comprehensive assignments
- 45+ Real-time industry case-studies
- 270+ Data Science tutorials
- 1:1 Career counselling with expert
- Practical knowledge which industry needs
- Industry-renowned Data Science certification
Your Data Science Journey Starts Here — Enroll Now
Master Data Science from Scratch
Join our hands-on Data Science online training crafted by industry veterans and build real-world skills. It’s not just a course, it’s a job-ready Data Science bootcamp.
Start Anytime (self-paced) |
Duration 100+ Hrs |
Access Duration 2 Years |
Price |
Enroll Now |
Course + Job Assistance (Resume Prep + Interview Prep + Mock Interview + Internship + Job/Placement Prep + Additional Real-time Projects + LOR) | Enroll Now | |||
Course + Job Assistance + Lifetime Course Access + Live Sessions with Instructor over Weekends: Live Mentoring + Doubt Clearance for 6 months | Enroll Now |
Why should you enroll in this Online Data Science Training Course?
- No experience needed—we’ll teach you from the ground up!
- Learn by doing Data Science projects that solve real problems
- Data Science experts are needed everywhere
- We explain things in easy words so everyone can understand
- Use the same tools that big companies use every day
- Open doors to exciting jobs and opportunities
- Learn from teachers with over 20 years of experience
- Meet and learn with other students just like you
- Learn how to use data to guess what might happen next
- Create things you can show to friends or future bosses
- Use data to help with health, environment, and more
- Be part of the future where data is key
- Study at your own pace, anytime and anywhere
- We’re here to help you succeed
- Get top-quality learning without spending a fortune
- Use your new skills to change the world for the better!
TechVidvan Data Science Course Objectives
Get ready to deep dive into the world of data!
In this Data Science training program, you will:
- Discover What is Data Science: Learn how data shapes our lives every day. Do you know that 90% of the world’s data was made in just last two years?
- Play with Real Data: Work on real-life projects, just like a real data scientist!
- Explore Machine Learning: Find how computers can learn and train from data and make smart guesses. It’s like teaching a computer to think!
- Use Cool Tools: Learn tools like Python and other special libraries that help you handle data easily.
- Solve Big Problems: Use data to find solutions to important problems in health, environment, etc.
- Build Your Own Projects: Create interesting projects that you can share with others and be proud of.
By the end of the online Data Science Certification course, you’ll have all the skills required to start your journey in data science.
Why should you learn Data Science?
Data Science is like having a special key to unlock secrets hidden in tons of information! Every day, we create huge amounts of data—every text message, every video watched, and every game played adds more and more.
By learning Data Science, you can turn this mountain of data into useful ideas. Imagine being able to predict what movies people will love, help doctors find better cures, or even make cool apps that everyone wants to use!
If you’re an engineering student or a professional new to data science, this field is full of exciting opportunities. You’ll learn how to teach computers to think on their own, find patterns that others might miss, and solve big problems that can make the world a better place.
- Unlock Hidden Secrets: Data Science helps you find patterns and answers hidden in big piles of data, just like a detective!
- High Demand for Skills: Companies all around the world need data scientists, so you can find exciting job opportunities.
- Solve Real Problems: Use data to make a difference in healthcare, the environment, technology, and more.
- Learn Cool Tools: Get hands-on with tools like Python, used by NASA and Google!
- Make Smart Decisions: Help businesses and organizations make better choices by understanding what the data tells us.
- Be Part of the Future: Data is growing every day—you can be at the front of new discoveries and innovations.
- Boost Your Problem-Solving Skills: Improve how you think and solve puzzles, which is helpful in everyday life.
- Versatile Career Paths: Work in many fields like sports, music, science, and more—wherever data is used!
- Create Amazing Projects: Build things like apps that recommend songs or predict weather patterns.
- Stand Out: Learning Data Science makes you unique and valuable in today’s technology-driven world.
What is Data Science?
Data Science, the hottest and highest-paid field on the planet, is like playing with data and generating hidden insights. Every day, world creates huge volume of information – photos, videos, social media, sensors, and more. We create 2.5 quintillion bytes of data ie 2.5 trillion GBs are made each day?
How can we handle all this data and generate meaningful information? That’s where Data Science comes into the picture. It helps us find hidden patterns and data-driven answers to drive business. Data scientists use the latest machine learning tools and techniques to identify patterns and generate relevant reports. The ultimate objective is to help businesses make the right decisions at the right time.
How your YouTube knows which video you might like, or how does Amazon suggest items you might want? That’s Data Science at work! It helps doctors find better treatments, makes games more fun, and even helps protect the environment.
In this Data Science online course, we’ll learn how to collect and understand data, use cool tools like Python, and solve real world problems. Join us, and let’s dive into the exciting world of Data Science together!
What to do before you begin?
Prerequisites of this Data Science Online Training Course
Great news! You don’t need to be a data expert to join us.
Here’s what you need:
- Basic Math Skills: If you can handle simple math like adding and subtracting, you’re good to go!
- Computer Know-How: Comfortable using a computer? Perfect! Browsing the internet and typing are all you need.
- Curiosity and Excitement: Bring your eagerness to learn and explore new things.
- Willingness to Learn Coding: Never coded before? No problem! We’ll start from the very beginning.
That’s it! No special experience or fancy degrees required. We’re here to help you every step of the way. So, are you ready to dive into the amazing world of Data Science with us?
Who should go for this Online Data Science Certified course?
This Data Science course is for anyone who is interested to know about data! If you’re:
- An Engineering Student: Discover how data can turn numbers into amazing solutions and solve real-world problems
- An Industry Professional: Add powerful skills to your toolbox to boost your work
- New to Data Science: We’ll guide you step by step on this exciting journey.
- A Curious Learner: Explore new ideas and answers to big questions
All you need is a desire and passion to learn and discover.
By enrolling in our Data Science training program, you can expect the following benefits:
Unlock a world of possibilities by joining this Best Data Science self paced course!
Here’s what you’ll gain:
- High-Demand Skills: Learn Data Science, one of the fastest-growing fields today. Companies everywhere need people who can analyse and use data.
- Hands-On Projects: Work on real-life problems just like a real data scientist. Imagine analyzing data to help save endangered animals or improve healthcare!
- Learn Cool Tools: Dive into Python and other powerful tools used by professionals. Did you know NASA uses Python for their space missions?
- Boost Your Career: Open doors to exciting jobs and opportunities. Data scientists are needed in every industry, from tech to sports.
- Solve Real-World Challenges: Use data to find answers to big questions about our world. Help make important decisions that can change lives.
- Build Your Own Portfolio: Create impressive projects that you can show to future employers or schools. Stand out from the crowd!
- Understand the World Better: Data is everywhere. Learn how to make sense of it and see patterns others might miss.
- Join a Learning Community: Connect with other curious minds. Share ideas, help each other, and make new friends.
- No Experience Needed: Start from the basics. Even if you’re new to data science, we’ll guide you every step of the way.
- Fun and Engaging Lessons: Enjoy learning through interactive activities and exciting challenges.
- Become a Data Detective: Find hidden clues in big piles of information. It’s like solving a mystery!
- Stay Ahead of the Curve: Be part of the future where data drives decisions in every field.
- Improve Problem-Solving Skills: Think critically and find smart solutions. These skills are useful everywhere!
- Flexible Learning: Learn at your own pace anytime and from anywhere. Fit the course into your busy schedule.
- Get Certified: Receive a certificate to show off your new skills. Add it to your resume or LinkedIn profile to show to employers.
- Make a Difference: Use what you learn to help others and make the world a better place.
Jobs after Learning TechVidvan Data Science Course
Great news! Learning Data Science opens the door to many amazing job roles.
Here are some job options you can look forward to:
- Data Scientist: Be the detective and find hidden answers from the data. Companies like Google and Amazon hire data scientists to improve their product quality.
- Data Analyst: Help businesses make smart decisions by studying data trends. Did you know that data analysts can help save companies millions of dollars?
- Machine Learning Engineer: Teach computers to learn from data. You could help create self-driving cars or smart home devices!
- Business Analyst: Use data to solve business problems and make companies better. Your ideas could change how businesses work.
- Data Engineer: Build systems that collect and store data. Imagine working with huge amounts of data like Facebook or YouTube!
- Artificial Intelligence Specialist: Work on cutting-edge AI projects. AI is used in healthcare, finance, and even space exploration!
- Statistician: Use math to understand data. You can help in sports, where statisticians help teams win games.
- Research Scientist: Explore new ways to use data in science. You could help discover new medicines or protect the environment.
- Data Visualization Expert: Turn complex data into easy-to-understand pictures. Help people see what the data means at a glance.
- Big Data Engineer: Handles massive amounts of data. Did you know that 90% of the world’s data was created in the last two years?
These jobs are in high demand, and companies are looking for people like you! With the skills you’ll learn in this online Data Science course, you’ll be ready to take on these exciting roles.
Start your journey now, and you could be the next big name in Data Science!
Our students are working in leading organizations
Online Data Science Training Course Curriculum
- Data Science Introduction
- Data Science Evolution
- Data Science Terminologies
- Difference between Data Science and AI/Machine Learning
- Business Requirement
- Data Preparation
- Types of Analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- Problem Formulation
- Data Collection
- Data Processing
- Data Analysis and Modeling
- Data Scientist
- Data Analyst
- Data Engineer
- Machine Learning Engineer
- Business Intelligence Analyst
- Business Analyst
- Data Science in Finance and Banking
- Data Science in Retail
- Data Science in Health Care
- Data Science in Logistics and Supply Chain
- Data Science in the Technology Industry
- Data Science in Manufacturing
- Data Science in Agriculture
- What is NumPy?
- Steps to Install NumPy in Python
- Steps to Install NumPy in PyCharm
- Creation of NumPy Arrays
- Basics of NumPy Arrays
- NumPy Array Attributes
- NumPy arange(), linspace(), & logspace() Functions
- Initialize Arrays with zeros(), ones(), full(), & eye() Functions in NumPy
- Compare NumPy Arrays
- any(), all(), & where() Methods in NumPy
- Arithmetic Operations on NumPy Arrays
- Statistical Functions in NumPy
- Reference vs View vs Copy in NumPy
- Array Concatenation in NumPy
- Concatenate Two NumPy Arrays
- How to Join Join NumPy Arrays Using concatenate(), stack(), vstack(), hstack(), and dstack()
- Split Arrays in NumPy
- What is Pandas?
- How to Install Pandas on Windows
- How to Install Pandas on PyCharm
- How to Download Datasets
- Pandas Series
- Properties of Series in Pandas
- Pandas Series Mathematical Operations
- Introduction to Pandas DataFrame
- How to Create DataFrames Using Excel, CSV, and Clipboard
- Ways to Create DataFrames
- Export Pandas DataFrame to CSV and Excel Files
- Pandas DataFrame Attributes
- DataFrame Slicing in Pandas
- Sorting in Pandas DataFrame
- Drop Duplicate Values in Pandas
- How to Handle Missing Data with fillna() & dropna()
- loc and iloc Methods in Pandas
- Apply Filter in Pandas DataFrame
- What is Advanced Data Analysis in Pandas?
- Pandas Join DataFrames
- Apply Join in Pandas DataFrame
- How to Use Join Without a Common Column
- Concatenate DataFrames in Pandas
- where() Function in Pandas
- Use where() in Pandas
- groupby() Method in Pandas
- Pandas Aggregate Functions
- SQL Equivalent Statements in Pandas
- Equivalent SQL Queries in Pnadas
- SQL Queries for Pandas DataFrames
- Use isin() and not isin() Methods in Pandas
- nlargest() Method in Pandas DataFrame
- Insert, Delete, and Update Method in Pandas DataFrames
- What is Matplotlib?
- How to Install Matplotlib in PyCharm
- How to Install Matplotlib Library in Python
- Design a Chart in Matplotlib
- Markers in Matplotlib
- Types of Markers in Matplotlib
- Lines and its Properties in Matplotlib
- Change Line in Chart Using Matplotlib
- How to Change Color and Font of Title, X-Axis & Y-Axis
- Change Font of Title and Axis in Matplotlib
- Matplotlib Legend Function
- Grid Lines in Matplotlib
- Add Grid Lines in Chart
- Matplotlib Subplot
- Plot Subplots in Matplotlib
- xticks(), yticks(), xlabel(), ylabel(), xlim(), ylim() Methods in Matplotlib
- Matplotlib Scatter Plot
- Cmap and ColorBar in Scatter Plot
- Create Vertical & Horizontal Bar Graph
- Plot Multiple Bars in Single Bar Graph
- Matplotlib Pie Chart
- Histogram Graph in Matplotlib
- Plot Histogram in Matplotlib
- Introduction to Seaborn
- Create Attractive Plots
- Statistical Plots: Box Plot, Heatmaps
- Pair plots and categorical plots
- What is Statistics?
- Descriptive and Inferential Statistics
- Terminologies of Statistics
- Types of Data
- What is Sampling?
- Types of Sampling Techniques
- Measures of Central Tendencies
- Measures of Spread
- Data Distribution Plot: Histogram, Scatter Plot, Box Plot
- Normal Distribution
- Z-Value
- Empirical Rule and Outliers
- Central Limit Theorem
- Skewness & Kurtosis
- Covariance & Correlation
- What is Probability?
- Axioms of Probability
- Conditional Probability
- Bayes Theorem
- Random Variables
- Probability Distributions: PMF, PDF, and CDF
- Common Probability Distribution: Binomial, Poisson, Exponential, Uniform, Log-Normal
- What is Hypothesis Testing?
- Types of Hypothesis Testing
- P-Value, Critical Region and Level of Significance
- Z-test, T-test, Anova Test and Chi test
- What is Machine Learning?
- Difference between Machine Learning and Artificial Intelligence
- Machine Learning Workflow
- Machine Learning Algorithms
- Building Machine Learning Model
- Clustering and Classification in ML
- Reinforcement Learning
- Regression: Linear and Logistic
- Difference between Supervised and Unsupervised Learning
- K-Means Clustering
- K-Nearest Neighbors (KNN)
- Prediction with Machine Learning Model
- Feature Engineering
- Techniques of Feature Engineering
- Support Vector Machine (SVM)
- How to Build SVM Models
- Decision Tree
- Naïve Bayes
- Gradient Boosting and XGBoost
- Introduction to Artificial Neural Networks
- History and Evolution of Deep Learning
- Applications and Use Cases of Deep Learning
- Convolutional Neural Networks
- Recurrent Neural Networks
- What is Computer Vision?
- OpenCV Installation using pip
- OpenCV Installation using PyCharm
- OpenCV imread() & imwrite() Functions
- Create Copy of an Images
- How to Show, Resize and Rotate an Image in OpenCV
- Merge Multiple Images in OpenCV
- Flip an Image in OpenCV Using Bitwise Not Function
- Change Image Color Using cvtColor Function in OpenCV
- Capture and Record Video Using OpenCV
- Capture Video From Webcam Camera in OpenCV
- Draw Line on Image & Video in OpenCV
- Draw a Circle and Put Text on Image in OpenCV
- add vs addWeighted Function in OpenCV
- Image Properties (Shape & Size) in OpenCV
- Crop an Image in OpenCV
- OpenCV hconcat() & vconcat() Functions
- OpenCV Concatenating Images
- Blur an Image in OpenCV
- Graphical Image Rotation Application in OpenCV
- Show/Open Dynamic and Multiple Images in OpenCV
- Dynamically Resize Image in OpenCV
- Open Video using Dialog Box
- Resize Video and Image in OpenCV with Dimensions
- Draw Different Shapes in OpenCV
- OpenCV Image Transformations
- Convert BGR Image to RGB Image
- Color Conversion in OpenCV
- Use Different Color Codes in OpenCV
- OpenCV Canny Edge Detection
- What is Natural Language Processing?
- Applications of NLP
- Text Preprocessing
- Text Classification
- Sentiment Analysis
- Introduction to Artificial Intelligence
- Introduction to Gen AI
- Introduction to Generative Adversarial Networks
- What is Power BI?
- How to Install and Setup Power BI
- Power BI Desktop UI
- Power BI Interface
- How to Identify and Connect to Data Sources
- How to Import Data
- What is Power Query?
- Power Query Editor
- Power Query Ribbon and Tabs
- How to Handle Missing Values and Clean Data
- How to Manage Data Source Settings
- How to Identify Fact and Dimension Tables
- Define Relationships
- Star Schema Design
- What is DAX?
- DAX Functions and Syntax
- Measures using DAX
- How to Create Calculated Tables
- How to Develop Calculated Columns
- Difference between Calculated Columns and Measures
- How to Build Your First Report
- Add and Customize Visuals
- How to Choose the Right Visualizations
- Reports with Themes and Formatting
- Interactive Features
- Publish Your Reports
- What is Big Data?
- Difference between Big Data and Data Science
- Five Vs
- Introduction to Hadoop
- How to Install Hadoop
- HDFS
- MapReduce
- Yarn
- Hive
- Flume
- Pig
- Sqoop
- HBase
- Introduction to Apache Spark
- RDDs
- Data Processing
- PySpark
- Spark SQL
Features of Online Data Science Course
Data Science Online Training FAQs
No worries! You don’t need any prior programming experience. We’ll start from scratch and teach you everything you need to know, especially using Python.
Just a computer with internet access! We’ll guide you on how to install free tools like Python and Jupyter Notebooks.
That’s okay! We’ll cover the basic math you need in a simple and easy-to-understand way. If you can handle basic algebra, you’ll do great.
Absolutely! This Data Science online course is designed for newcomers. We’ll explain everything in simple terms and build up your knowledge step by step.
Yes! You’ll work on real-life projects like analyzing weather data or creating a simple movie recommendation system. It’s a fun way to learn by doing.
You’ll have access to helpful instructors and a community of fellow learners. We’re here to answer your questions and cheer you on!
Yes, you’ll receive a certificate that you can share with employers or add to your resume to show off your new skills.
Data Science skills are in high demand. You’ll open doors to exciting jobs like Data Analyst, Machine Learning Engineer, and more.
Definitely! You’ll have ongoing access to all the lessons and resources so you can revisit them anytime.
The complete course duration is 90 hours. Plan to spend about 20 hours per week on lessons and projects to get the most out of it.