A Comprehensive Learning Path to Become a Data Scientist in 2021!
Are you Ready to Become a Data Scientist in 2021?
A new year beckons! New resolutions to become a data scientist have to be made! And surely things can only get better after the tumultuous ride that’s been 2020?
And what better way to end this year and welcome the new one than planning out your entire career in one place?
That’s right – we are back with the most in-demand learning path in the data science community!
The 2020 edition of the Data Science Learning Path!
Every year we release the data science learning path which is viewed and loved by thousands of data science aspirants all around the globe. So this keeping in mind, the popular demand, suggestions, and updates, here’s the data science learning path for 2021.
The learning path for 2021 is the ultimate and most comprehensive collection of resources put together in a structured manner. This learning path is for anyone who wants to make a career in data science. So whether you are a fresher, have a few years of work experience, or are a mid-level professional – this data science learning path is for you.
If you are tired of going through thousands of unstructured resources and trying to make sense? Not anymore. Let’s begin!
What’s new in the 2021 Data Science Learning Path?
Each year the experts at Analytics Vidhya update and revise the data science learning path by taking into consideration the latest industry practices and trends, recent researches, and suggestions from the community. So what’s new this year?
1. Extended Storytelling Skills – Storytelling is more of an art than a skill. A good data scientist is someone who can turn insights into action with the help of visualization. You’ll get familiarized with different visualization tools, techniques, and strategies.
2. Model deployment – It is perhaps the most important data science topic that is left out of most data science courses. Any data science model is essentially wasted unless it is deployed on an application. This learning path will introduce you to high-quality resources to gain this important skill.
3. Comprehensive Unsupervised learning – Dealing with unstructured data? Unsupervised Learning is the way to go. In this edition of the learning path, we have created a separate module for this topic so that you can perfect it!
4. More exercises – What’s better than taking up a course just for the sake of it? We have incorporated a high number of exercises and assignments so that you can tickle your brain cells and give a boost to your memory.
5. Added Projects and Jobs section – Projects are the all-powerful way to convert conceptual and theoretical knowledge into practical knowledge. We have introduced a new section of projects and jobs which will help you navigate through the industry.
You can access the complete and most comprehensive learning path to become a data scientist in 2021 here. You would need to register yourself on the Courses platform to enroll yourself. This will enable you to keep track of what you have covered as you progress in your machine learning journey.
Summary of the Data Science Learning Path 2021
Data Science Toolkit – It’s the start of your journey to becoming a successful data scientist! In this month, you will start your journey in the field of data science and learn about the most common and frequently used data science tools – Python and its libraries such as Pandas, NumPy, Matplolib, and Seaborn.
Data Visualization – As you have cleared the basics, we will begin with the most crucial skillset of a data scientist. The aim of this month is to familiarize you with different data visualization tools and techniques such as Tableau. This month will also be a starting point of your SQL journey.
Data Exploration – The data is hidden with important information. Bringing out this information in the form of insights is data exploration. In this month, you will learn how to explore your data with Exploratory Data
Analysis (EDA). Along with this, you will also understand the important concepts of statistics required to become a data scientist.
Basics of Machine Learning and the art of storytelling – Now let’s get down to actual machine learning! From this month onwards, you will start your Machine Learning journey. In this month, you will cover basic ML techniques and the art of storytelling using Structured thinking.
Advanced Machine Learning – Done with basics? It’s time to turn up the notch! The goal of this month is to cover advanced machine learning algorithms. You will also learn about feature engineering and how to work with Text and Image data.
Unsupervised Machine Learning – Dealing with unstructured data can be challenging so let’s jump into the solution! In this month, you will learn about unsupervised machine learning algorithms like K-Means, Hierarchical Clustering, and finally deep dive into a project!
Recommendation engines – Curious how Netflix, Amazon, Zomato give such amazing recommendations? It is time for you to delve into recommendation systems. In this month, you will learn different techniques to build recommendation engines. We have also got an exciting project for you fellas!
Working with Time Series Data – Organizations around the world depend heavily on time-series data and machine learning has made the scenario even more exciting. In this month, you will learn how to work with Time Series data and different techniques to solve time series related problems.
Introduction to Deep Learning and Computer Vision – Deep Learning and Computer Vision is at the forefront of the most happening projects in the field of AI be it Self driven cars, mask detection cameras, and more. From this month onwards, you will start your journey in the field of Deep Learning. You will learn basic deep learning architectures and then solve different computer vision projects.
Basics of Natural Language Processing – Do you wonder how Social media giants like Twitter, Facebook, Instagram process incoming text data? This month will move your focus to the field of Natural Language Processing (NLP). Here you will learn more deep learning architectures and solve NLP related projects.
Model Deployment – What is more essential than building a data science model? Deploying it! In this month, you will learn different ways to deploy your models. You’ll get to spend time on exploring streamlit for model deployment, AWS, and also get to deploy the model using Flask.
Projects and Jobs – The time has finally come to convert all your hard work into fruition! In this final month, you will do different projects and start applying for internships or jobs.
As mentioned above, You can access the full data science learning path here. Register yourself and begin your machine learning journey today! You can track your progress throughout the year as you check off milestones and inch closer to your dream role.
We have also provided an illustrated version of this data science learning path below which paints a month-by-month picture. You can print this out and use this as a checklist. And if you put forward your best efforts and follow this learning path – you’d be in a great position to start cracking data science interviews by the end of 2021.
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