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How to Learn Data Science in 10 weeks?

Isha Sharma
Published: July 5, 2022

The magic of “Data Science” has exploded in the entire market and has become a major wagon for all scales of businesses. Today, the decisions companies are making along with the forecast are solely dependent on data science. The field of data science has grown more than 3x folds, especially during the recent pandemic, as everyone was forced to work remotely, and thus it has opened many doors of opportunities for companies and working professionals to switch or start their careers in this field.

Roadmap to Data Science - 10 Weeks Plan

Recent stats have also suggested that almost 40% of companies have slashed their unwanted expenditure and that’s how more than 50,000 jobs have been generated in this field. Even if you talk about current stats, there are more than 1 lakh jobs available alone in India and more than 10 lakhs are there at a worldwide level. This clearly indicates that the scope in the field of data science is going to be glorious in the upcoming years. Now, the question arises is how to learn data science in 10 weeks? Learning could be fun and interactive only if you’ve chosen the right path and resources. In this article, we’ll see the steps, procedure, material, and allocation of time for learning data science right from the beginner’s level. Let’s find out:

But, before we move ahead, you must understand why you should opt for Data Science as a career point of view.

Why Choose Data Science?

It has become one of the hottest jobs out there in the market, as we’re going digital, more companies are relying on playing their major games by predicting the market forecast. Talking about the payout, it’s much better than most of the jobs out there in the market and it helps individuals to brush up on various skills such as mathematics, data visualization, analytics, etc.

Today’s scenario is that the demand for data science jobs is more but the candidates aren’t sufficient to fulfill those requirements and this has led to a major shift from a career perspective. Even employees are shifting their careers by learning data science. By this, you can assume how big the scope is and one thing is for sure, this demand is not going to decrease in the upcoming years.

Now, let’s get back to our today’s agenda and check out, How to Learn Data Science in 10 weeks? 

Week 1

Getting Started with Python

For those who don’t know Python is a high-level, multipurpose, cross-platform programming language that runs on multiple OS (such as Windows, Linux, and macOS) and it’s free to use. You can also go through the course Python Programming Foundation – Self-Paced and learn about Python Fundamentals.

So, the easiest way to start learning Python is to start within the following sequence:

You can also visit the Python IDE for best practices.

Week 2

Data Analysis with Python

After getting the basics of Python, it is a must to understand the core principles of data analysis, which is majorly used by companies today. All of the forecasts, predictions, and decisions that companies do make are solely based on data analysis patterns. For best practice, you can check out the Data Analysis with Python – Self-Paced course that has been tailed to equip you with logical and analytical handling. Now, to help you with this in detail, below is the list that you should consider in the next phase.

Importing Data

  1. How to import an Excel file in Panda?
  2. How to read Text files in Python using Panda?
  3. How to read JSON files with Panda?

Week 3

Data Visualization

Data Processing Methods

  1. Understanding Data Processing
  2. Pandas DataFrame
  3. Data Cleaning (Overview)
  4. Slicing, Indexing, Manipulating, and Cleaning Pandas Dataframe
  5. Working with Missing Data in Pandas

Week 4

Exploratory Data Analysis

Week 5

Web Scraping

Project Guide for Web Scraping

  1. Web Scraping from Wikipedia using Python
  2. Scraping Amazon Product Information using Beautiful Soup
  3. Amazon Customer Review
  4. Scrape LinkedIn using Selenium & Beautiful Soup

Week 6


Hypothesis Testing

Mathematical Explanation in ML

ANOVA Test in Python


Week 7

Machine Learning

Machine Learning is one of the fanciest words that we hear these days which is also termed as new generation technology and has dominated this whole world in the era of technology. You name any device that exists today that is fully focused on AI, ML, and DL. Interestingly, the scope of this technology is also comparatively high in the market and the demand is going to explode by nearly 33% by the end of 2025. This is one of the reasons why people are shifting their careers to this field and they’re actively learning about this technology. If you wish to learn it from scratch, you may refer to Machine Learning Basic and Advanced – Self-Paced course that has been tailored to provide data processing methods in python to make you an industry expert. meanwhile, let’s look at the journey that you’re going to explore in the 7th week of data science.

Supervised Learning

Unsupervised Learning

Decision Tree

Week 8

Deep Learning

Project to Work 

Week 9

Natural Language Processing

Project to work 

Natural Language Processing Libraries

  • Scikit-Learn
  • Natural Language Toolkit
  • Pattern
  • Textblob
  • Quepy

Text Preprocessing

Featured – NLP

Week 10

Since you’ve finished your journey right from Week 1 – Week 9, now is the time for you to take active participation to work in-depth in data science, this can be done by opting through Data Science – Live Course that will take you forward in becoming a class-apart data science expert. Whereas, take a look at some projects where you can understand the basics of data science and will definitely be going to help you to brush up on your skills. We have compiled a list of categorized projects/ideas for better clarity. Let’s have a look:

Data Analysis Project

  • Data Analysis for Olympics: This project will drive you through various data and will show how you can implement and use best cases while giving tasks for data analysis.

Data Visualization Project

Web Scraping Project 

Machine Learning Projects (Beginners)

Machine Learning Projects (Advanced)

Deep Learning Projects