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Ultimate Data Science Bootcamp in Python with 5 Projects




Data Science is an interdisciplinary field that uses scientific methods and algorithms to extract clean information from raw data to formulate actionable insights.

This field is growing so rapidly and revolutionizing so many industries.

It has incalculable benefits in business, research, and our everyday lives.

Your route to work, your most recent Google search for the nearest coffee shop, your Instagram post about what you ate, and even the health data from your fitness tracker are all important to different data scientists in different ways.


Sifting through massive lakes of data, looking for connections and patterns, data science is responsible for bringing us new products, delivering breakthrough insights, and making our lives more convenient.

It encompasses a wide range of topics:-

1. Python.

2. Statistics.


3. Machine Learning.

4. Mathematics.

5. Data Visualization.

6. Data Cleaning.


7. Hypothesis Testing.

8. Query Analysis.

Each of these topics builds on the other. You need to acquire all the skills in the right order.

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You are at the right place!!!


Welcome to this online resource to learn Data Science Skills.

This course will really help you to boost your career.

This Data Science Course begins with the most basic level and goes up to the most advanced techniques step by step.

Even if you don’t know anything in advance, this course will make complete sense to you.


In this  Data Science Course you will learn about the following:-

1. The fundamentals of python programming language:- variables, data types, loops, and conditionals.

2. Python data structures:- lists, tuples, dictionaries, sets, stacks, queues.

3. Object-oriented programming in python.


4. Regular Expressions.

5. Numpy library.

6. Pandas library.

7. grouping and filtering operations for data analysis.


8. Basic and Advanced visualizations.

9. Descriptive statistics.

10. Inferential statistics.

11. Hypothesis Testing.


12. Exploring Dab and Sweetviz library.

13. Linear Regression theory and practical.

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14. Logistic Regression theory and practical.

15. Clustering analysis.


There are lots and lots of exercises for you to practice In this Data Science Course and also a  5 Bonus Data Science Project “Player’s Performance Reviewer,” “Start-ups Case Study and Analysis,” “Movie Recommender Engine,” “Global Cost of Living Analysis” and “Customer Segmentation Engine.”

In this Player’s Performance Reviewer project, you will analyze the performance metrics of players based on their ground positions, skills, nationality, clubs, age, height, weight, and understanding the major factors driving the performance of these players.

In this Start-ups Case Study and Analysis project, you will analyze the Indian Startups and Understand the Startup Ecosystems in India to answer some Interesting Questions. Try to find out the Major Investors and Startups.

In this Movie Recommender Engine project, you will learn How to analyze a Movie Database to find useful insights and Recommend Movies.


In this Global Cost of Living Analysis project, you will learn how to perform Geospatial Analysis and understand some major factors determining the quality of life in different world cities. And also learn to perform Comparative analysis.

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In this Customer Segmentation Engine project, you will divide the customer base into several groups of individuals that share a similarity in different ways relevant to marketing, such as gender, age, interests, and miscellaneous spending habits.

You will make use of all the topics read in this Data Science Course 2021.

You will also have access to all the resources used in this Data Science Course 2021.


Enroll now and become a python pro!!!

Who this course is for:

  • Python Developers
  • Beginners for Data Science
  • Data Analysts
  • Data Scientists

What you’ll learn

  • Fundamentals of Data Science
  • Data Science Capstone Projects
  • Grouping and Filtering Operations for Data Analysis
  • Object-Oriented Programming in Python
  • Hypothesis Testing
  • Basic and Advanced Data Visualization
  • Clustering Analysis

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  • No prior knowledge is required.
  • Understanding Programming Language
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