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About Introduction to Data Science Course

Getting Started with Data Science

 What is Data Science? Why has it become so popular recently? What are some of the popular data science applications? And more importantly, how can you get started with learning data science from scratch?

 Are you looking for the answer to these questions? Frustrated by the lack of structured data science learning? You’ve come to the right place!

 Data science is ubiquitous right now. Organizations are splurging to integrate data science solutions in their daily processes. It’s a great time to learn data science and get ready for your first industry role!

 This course, curated by experienced data science instructors and experts at Analytics Vidhya, will cover the core concepts you need to know to crack data science interviews and become a data scientist!


Why pursue Data Science:

  • Data Science is ubiquitous! It is the hottest field in the industry right now
  • Data Scientists are one of the most demanded professionals
  • There are so many data science algorithms to build predictive models, such as linear regression, logistic regression, decision trees and random forests. Keep learning, keep growing!
  • The potential of data science is limitless - spanning across industries, roles and functions


What will you learn in the ‘Introduction to Data Science’ course?

  • Understand what data science is
  • The various and diverse applications of data science
  • Common data science terminologies
  • Python for data science – the most popular data science programming language
    • Python from scratch – no previous programming experience required!
    • Understand how to use Jupyter Notebooks for data science
    • Get familiar with popular Python libraries for data science like Pandas and NumPy
  • Core Statistics for data science - Descriptive Statistics and Inferential Statistics
    • Measures of central tendency - mean, median, mode
    • Standard deviation
    • Outlier detection
    • Correlation
    • Hypothesis Testing
    • Confidence Intervals & margin of error
    • Chi-squared test
  • Probability concepts for data science
    • Introduction to Probability
    • Central Limit Theorem
    • Bernoulli Trials
  • Introduction to core machine learning algorithms for data science
    • Types of predictive models in data science
    • Overview of end-to-end data science process
    • Data extraction and data cleaning
    • Basics of machine learning model building
    • Linear regression
    • Logistic regression
    • Decision trees
    • Random forests
    • And much, much more!
  • Plenty of hands-on examples and multiple real-world industry-relevant data science projects

Why should you take the Introduction to Data Science course?

  • Ideal way to start your Data Science Journey The ‘Introduction to Data Science’ course has been created keeping a data science beginner in mind. This course provides everything you need to start your journey in data science.

  • Easy to understand content The biggest challenge beginners face is that most courses explain data science as a difficult mathematical subject. Not us! We simplify data science and machine learning with easy to understand videos and help you build an intuition on data science concepts.

  • Experienced Instructors with Data Science know-how All the material in this ‘Introduction to Data Science’ course was created by Analytics Vidhya instructors who bring in immense experience of data science with them. All our instructors have years of experience in data science and analytics.

  • Industry collaboration The entire course has been vetted and created along with experts from the data science industry. This ensures relevance in industry and enables you with the content which matters the most.

  • Real life projects and problems for Data Science All projects in the course are based on real life data science problems. No academic datasets are being used to ensure that you are ready for real life problems in the data science industry.

Highlights of Introduction to Data Science Course

  • 60+ Hours of Comprehensive content

    Covering Introduction to Python, Statistics, Predictive Models and Data Science fundamentals

  • 4 Real Life Projects from Data Science Industry

    To prepare you for Data Science Career and Industry

  • Live Q & A Session

    Interact with experts on live chat for 1 hour daily.

Here's what our students have to say about our Introduction to Data Science course

  • I would definitely recommend this!

    Naren Bakshi

    The course covers all the 3 aspects of Data science, i.e Programming, Statistics, and the ML part. It also has 2 final projects to let you practice the newly...

    Read More

    The course covers all the 3 aspects of Data science, i.e Programming, Statistics, and the ML part. It also has 2 final projects to let you practice the newly learned skills. It's a 10/10 from me 👍

    Read Less

  • Just the right course for beginners like me

    Umang Verma

    I had been trying to get into data science on my own for some time, but this course provided a very good structure and the hands on experience needed to star...

    Read More

    I had been trying to get into data science on my own for some time, but this course provided a very good structure and the hands on experience needed to start the journey in a simple manner. The lectures are easy to understand and the course covers basics of Python, Statistics and Predictive Modeling.

    Read Less

  • Great course for who is just getting start with python an...

    Leonardo Silva

    Easy going course with hands-on exercises.

    Easy going course with hands-on exercises.

    Read Less

  • Very well organized

    Abhilash G

    very organized easy to follow course

    very organized easy to follow course

    Read Less

Project - Identify best Insurance agents

Predict performance of Insurance agents using past data

Your client is looking for help from data scientists like you to help them provide business insigths using their past recruitment data. They want you to predict the target variable for each potential agent, which would help them identify the right agents to hire.
Project - Identify best Insurance agents

Project - Sales Prediction for a large Supermarket

Use Data Science to predict sales of products across Supermarkets

The data scientists at BigMart have collected sales data for 1559 products across 10 stores in different cities for an entire year. Also, certain attributes of each product and store have been defined. You will build a predictive model to forecast the sales of each product at a particular store.
Project - Sales Prediction for a large Supermarket

Project - Predict survivors from Titanic tragedy (In-class)

Use data science to identify survivors

You will analyse what kind of people were likely to survive in Titanic tragedy. You will apply machine learning algorithms to predict which passengers survived the tragedy.
Project - Predict survivors from Titanic tragedy (In-class)

Common Questions Beginners in Data Science ask

  • I have no programming experience. Would I need to learn Python to learn data science?

    Programming is an essential aspect of being a data scientist or a data science professional. And Python is the market leader in this space. Organizations globally are adopting Python as their go-to language, including big tech firms like Spotify, Netflix, Facebook, among others.

    Python consistently ranks top in global data science surveys and its widespread popularity will only keep on increasing in the coming years.

    Over the years, with strong data science community support, this language has obtained a dedicated library for data analysis and predictive modelling.

    And don’t worry! Python is a very easy language to learn and we cover it from scratch in the course. So you don’t need to have any prior programming knowledge to master Python!

  • Do I need to know statistics before taking this course?

    No! Statistics is the backbone of data science and we understand that. We have designed an entire comprehensive module on statistics which we cover in the course.

    We will cover both descriptive statistics and inferential statistics in detail, along with how to implement each concept in Python. And once you’ve learned and practiced statistics concepts, we will then jump to data science modelling.

  • What kind of projects can I take up after this course?

    You can take up a variety of data science projects! Since this covers both regression and classification algorithms, like linear regression, logistic regression and decision trees, you’ll be well equipped to apply your data science and Python skills on real world projects.

    We recommend you pick up the projects we’ve curated on the DataHack platform. These projects will hone your data science skills and enhance what you have learned in the Introduction to Data Science course.

  • Can I add the projects covered in this course in my resume?

    Of course! Projects are among the first things a hiring manager or recruiter looks for in a data science resume. The more projects you add, the stronger your chance of landing your dream role.

    As mentioned above, you can head to the DataHack platform and pick up projects from there. Practice is key in data science!

  • Will this course help me clear data science interviews?

    This course will help you build a solid base for data science. You will learn a new programming language (Python), the backbone of data science (statistics), and core predictive modeling techniques.

    As a next step, you should go through our course - Ace Data Science Interviews.

Instructor(s)

  • Kunal Jain

    Founder & CEO

    Kunal Jain

    Kunal is the Founder of Analytics Vidhya. Analytics Vidhya is one of largest Data Science community across the globe. Kunal is a data science evangelist and has a passion for teaching practical machine learning and data science. Before starting Analytics Vidhya, Kunal had worked in Analytics and Data Science for more than 12 years across various geographies and companies like Capital One and Aviva Life Insurance. He has worked with several clients and helped them build their data science capabilities from scratch.
  • Neeraj Singh Sarwan

    Neeraj Singh Sarwan

    Neeraj is working at Fractal Analytics. Prior to that Neeraj was a data scientist with Analytics Vidhya. He has extensive experience in converting business problems to data problems. He has previously conducted several corporate trainings and is also an avid blogger. He's a graduate of IIT-BHU and will be your instructor for the Python and Modeling modules.

FAQ

  • Who should take this course?

    This course is designed for people looking to learn data science. We will start by understanding the basic concepts from scratch, and then go on to solve case studies using data science concepts.

  • When will the classes be held in this course?

    This is a self paced course, which you can take any time at your convenience over the 6 months after your purchase.

  • How many hours per week should I dedicate to complete the course?

    If you can put between 6 to 8 hours a week, you should be able to finish the course in 4 to 6 weeks.

  • Do I need to install any software before starting the course ?

    You will get information about all installations as part of the course.

  • What is the refund policy?

    The fee for this course is non-refundable.

  • Do I need to take the modules in a specific order?

    We would highly recommend taking the course in the order in which it has been designed to gain the maximum knowledge from it.

  • Do I get a certificate upon completion of the course?

    Yes, you will be given a certificate upon satisfactory completion of the course.

  • What is the fee for this course?

    Fee for this course is INR 7,999

  • How long I can access the course?

    You will be able to access the course material for six months since the start of the course.

Customer Support for our Courses & Programs

We are there for your support when you need!

  • Phone - 10 AM - 6 PM (IST) on Weekdays (Mon - Fri) on +91-8368808185

  • Email [email protected] (revert in 1 working day)

  • Discussion Forum - answer in 1 working day