A comprehensive learning path to becoming a data scientist in 2021!

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A new year is calling! New Resolutions Must Be Made To Become A Data Scientist!! And could things possibly only get better after the tumultuous journey that has been 2020?

And what better way to end this year and welcome the new one than to plan your entire career in one place?

That's how it is, We're back with the most requested learning path in the data science community!!

The edition 2020 of the data science learning path!

data science learning path

Every year we launch the data science learning path that is seen and loved by hundreds of aspiring data science around the world.. Then, taking into account popular demand, suggestions and updates, here's the data science learning path for 2021.

The learning path for 2021 is the definitive and most comprehensive collection of resources put together in a structured way. This learning path is for anyone looking to pursue a career in data science. Then, whether i am a beginner, have a few years of work experience or are a mid-level professional, this data science learning path is for you.

Tired of going through hundreds of unstructured resources and trying to make sense? Not anymore. Let's start!

What's new in the data science learning path of 2021?

Every year, DataPeaker experts update and review the data science learning path with the latest industry practices and trends in mind, recent research and community suggestions. Then, What's new this year?

1. Expanded storytelling skills – Telling stories is more of an art than a skill. A good data scientist is someone who can turn information into action with the help of visualization.. You will become familiar with different tools, visualization techniques and strategies.

2. Model deployment – It is perhaps the single most important data science topic left out of most data science courses.. Any data science model is essentially wasted unless it is implemented in an application. This learning path will introduce you to high-quality resources for obtaining this important skill..

3. Unsupervised comprehensive 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 you can refine it.

4. More exercises – What's better than taking a course just for the sake of it? We have incorporated a large number of exercises and tasks so that you can promote your brain cells and promote your memory.

5. Projects section and added jobs – Projects are the all-powerful way to turn conceptual and theoretical knowledge into practical knowledge. We have entered a new section of projects and jobs that will help you navigate the industry.

You can enter the full and more complete learning path to become a data scientist in 2021 here. You should register on the Courses platform to enroll. This will allow you to keep track of what you have covered as you go on your machine learning journey..

Data Science Toolkit – It's the start of your journey to becoming a successful data scientist!! In this month, you will begin your journey in the field of data science and learn about the most common and frequently used data science tools: Python and its libraries like Pandas, NumPy, Matplolib y Seaborn.

Data visualization – Once you've clarified the basics, we'll start with the most crucial skill set of a data scientist. The goal of this month is to familiarize you with different data visualization tools and techniques, como Table. This month will also be a starting point for your journey to SQL.

Data exploration – Data is hidden with important information. Getting this information out in the form of insights is data exploration. In this month, learn to explore your data with Exploratory Data
Analysis (EDA). along with this, you will also understand the important statistical concepts required to become a data scientist.

Machine learning basics and the art of storytelling – Now let's get to real machine learning!! From this month, your machine learning journey will begin. In this month, cover basic machine learning techniques and the art of storytelling using structured thinking.

Advanced machine learning – Are you done with the basics? Time to go up the notch! This month's goal is to cover advanced machine learning algorithms. You will also learn about function engineering and how to work with text and image data..

Unsupervised machine learning: Dealing with unstructured data can be challenging, So let's jump to the answer! In this month, learn about unsupervised machine learning algorithms like K-Means, Hierarchical Clustering y, to end, Will delve into a project!

Recommendation engines – Curious how Netflix, Amazon, Zomato offer such amazing recommendations? It's time for you to dig deep into the recommender systems. In this month, you will learn different techniques to build recommendation engines. We also have an exciting project for you!, friends!

Work with time series data – Institutions everywhere rely heavily on time series data and machine learning has made the scene even more exciting. In this month, you will learn to work with time series data and different techniques to solve problems related to time series.

Introduction to deep learning and computer vision – Deep learning and computer vision are at the forefront of the latest projects in the field of artificial intelligence, whether they are autonomous cars, mask detection cameras and more. From this month, will begin your journey in the field of Deep Learning. You will learn basic deep learning architectures and then solve different computer vision projects.

Natural language processing basics – Wondering how social media giants like Twitter, Facebook and Instagram process incoming text data? This month your focus will shift to the field of natural language processing (PNL). Here you will learn more deep learning architectures and solve projects related to NLP.

Model deployment – What is more essential than building a data science model? Implementing it! In this month, you will learn different alternatives to put your models into practice. Spend time exploring streamlit for model deployment, AWS, and you can also put the model into practice with Flask.

Projects and jobs – The time has finally come to turn all your hard work into reality!! In this last month, you will do different projects and start applying for internships or jobs.

As mentioned previously, you can enter the complete data science learning path here. Sign up and start your machine learning journey today!! You can track your progress throughout the year as you mark milestones and get closer to your dream role.

We also provide an illustrated version of this data science learning path below., showing an image month by month. You can print it out and use it as a checklist. And if you put forth your best efforts and follow this learning path, You'll be in a great position to start deciphering data science interviews for research purposes. 2021.

data science learning path infographic

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