Master Data Science Course in 2025 with GUVI’s Industry-Leading program

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Data Science Course

Master Data Science Course in 2025 with GUVI’s Industry-Leading program

GUVI’s Data Science Course is a top-tier tech course designed to set you up for a high-paying career, and it is certified by IIT-M Pravartak, taught by experienced industry professionals, including former PayPal employees and With expert mentorship from leading data specialists, this Data Science Course not only sharpens your skills but also connects you with Fortune 500 companies, and the goal is to help top organisations find the right talent—and that could be you!

Data Science Course Overview

  • This Data Science Course has been designed by subject matter experts & approved by NASSCOM.
  • Classes are conducted online + lifetime recorded videos
  • Unlimited access is given to practice on CodeKata, WebKata, and IDE.
  • One-on-One with Mentors
  • Special sessions for Ask-me-Anything with Industry Experts
  • IIT-M Pravartak Certification for Advanced Programming Professional
  • Placement Guidance
  • A digital portfolio through “Github”
  • EMI options available (up to 12 months).  For Refunds & Registrations: kindly refer to the link: T&C

Tools Covered (Data Science Course)

  • Data Science
  • Python
  • My Sql
  • Tableau
  • Power BI
  • NLP
  • Machine Learning
  • Data Visualization
  • Computational Thinking
  • Numpy
  • Pandas

Instructors (Data Science Course)

  • Mr. Sudarshan S R, Associate Professor, IIT Ropar
  • Mr. Koushik Krishnan – Data Science Analyst at Credit Suisse
  • Mr. Bala Chandar—Data Scientist, US-Based Client
  • Mr. Abhishek, Data Scientist, Bosch
  • Mr. Vinish Vivek—Consultant—Python
  • Mr. Shyam Kumar – Machine Learning Solution Lead
  • Ms. Neeru Dubey—Research Scientist
  • Mr. Thillaikkarasan M. – Lead Data Scientist
  • Mr. Jagadeesh Rajarajan – Senior Staff Engineer, Data Science
  • Mr. Amit Kumar Verma – Applied Research Scientist at Core CLM, (Seattle, USA), PhD IIT Ropar
Happy Learners

Course Syllabus (Data Science Course)

This course has been designed to make you aware of real-world data science skills through hands-on projects. You’ll work with top technologies like Python, MongoDB, Pandas, NumPy, Tableau, and Power BI, and you gain practical experience every step of the way. Join this growing community of emerging data scientists who share their expertise to uncover trends and manage data like true analytics pros. It has a total of 23 modules, which are given below.

Since they have the essential basics of python and you will see some advanced concepts like Comprehensions, File handling, Regular Expressions, Object-oriented Programming, Pickling and many more essential concepts.

You will explore the need for Algorithmic Thinking and the necessity of efficient coding, They will drive through Data Structures and Algorithms along with Memory Management Techniques

Since You need to handle huge amounts of data, you will be implementing data handling techniques with Pandas library. And you will explore the different miscellaneous functions of Pandas library in detail.

You will drive into the SQL-based database. You will learn the basics of SQL queries, schemas and normalization.

You will continue into the SQL-based database. You will learn the SQL Advanced queries, join, Date and Time Functions and Sub Queries.

You will go through Probability and Statistics whereas they are key to understand, process and interpret the vast amount of data, You will deal with the basics of probability and statistics like Probability theory, Bayes theorem, distributions etc and their importance. Besides that, You will do hands-on with Numpy upon those concepts

You will continue with statistics and probability and You will deal with descriptive and inferential statistics along with Hypothesis testing and a lot of other relevant statistics methods

Data Visualization is used to understand data in a visual context so the patterns, trends and correlations in the data can be understood. You will do a lot of visualization with libraries like Seaborn, Matplotlib etc in turn that leads to effective storytelling.

It is always needed to analyze the data and preprocess it, since the real world data is not always industry ready, so in this week You will be dealing with a lot of data cleaning and Exploratory data Analysis techniques which is a very crucial stage for any data science project.

Real world data is always messy and it’s very important to understand the statistical nature of data. Exploratory Data Analysis process, involving the preliminary examination of data to understand its characteristics, uncover patterns and identify potential insights.

You are going to explore the need of machine learning and its types, Algorithms when to use and how to use essential mathematical intuition along with Evaluation metrics. You will see in detail about regression algorithms.

In continuation to the ML algorithms we are going to see in detail about different classification algorithms along with mathematical intuition and evaluation metrics

You are going to explore classification algorithms like tree based algorithms in detail like how to interpret trees, pruning and ensemble methods like bragging and boosting etc

After dealing with a lot of Supervised machine learning algorithms You will compare and get to know when to use what, Besides that You will deal with the do’s and don’ts while training an ML model.

Now You will explore Unsupervised learning algorithms, why unsupervised ?, when to use it and as well as the essential mathematical intuition

As You move on to more complex problems, such as object recognition and text analysis, our data becomes extremely high dimensional, and the relationship becomes nonlinear. To accommodate this complexity, You move on to building more complex models that resemble our brain.

Now that You have a better theoretical understanding of deep learning models, You will spend this module implementing some of these algorithms in PyTorch

Now that You have the basic understanding of PyTorch, You will now dive into discussing the implementation details of a few state-of-the-art deep learning architectures in PyTorch

You are going to explore Natural Language Processing (NLP). Given the fact that we have a decent understanding of Machine Learning and Deep Learning, You can now explore the powerful ways to handle the NLP use cases

Having a basic understanding of NLP use cases, now You will dive into the CoPputer Vision FundaPentals. You will discuss state-of-the-art CV problePs and their solutions with deep learning.

Having a good understanding of ML, DL and various use cases, You will now discuss the platforms through which You can securely deploy these powerful models on production level. More specifically; You will discuss the fundamentals of AWS services and how to use them efficiently

This whole week You are going to work on industry projects which are currently in demand in the guidance of industry experts

Eventually, it’s time to attend the mock interviews which will be conducted by the industry experts like Data scientists, IIT professors and renowned HR’s inorder to mould you in every area possible

Frequently Asked Questions

Any aspirant with a minimum High School qualification and an interest in Data Science is eligible for this course. Guvi experts would gladly take it forward.

Data Science is a course of 3 months with weekday classes & 5 months with weekend live classes

This is a project-based curriculum, every student has to work & submit the projects with our Industry experts’ guidance. MCQs & assessments help evaluate your performance. After the successful completion of the course, GUVI will grant a globally recognized course completion certificate.

This Data Science program is offered as Weekend/Weekday Live classes. They also provide the recordings of the sessions.

You can submit the projects either Online or Offline.

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