Free Data Science Online Courses for Beginners to Join in 2022

by Kinsley D. Education

Greetings, friends! Data Science is one of the most in-demand talents in today's digital industry, with organisations of all sizes looking for skilled Data Scientists to help them make sense of the huge amounts of data they collect every day in order to boost sales, profits, and overall company processes.

You've come to the correct place if you want to learn Data Science and Data Analysis and are seeking for some free online training courses to get started.

I already published the top Data Science courses, and in this article, I'll share free Data Science courses for both beginners and experienced programmers from Udemy, Careerera, DataCamp, and freeCodecamp.

What is data science, why is it so popular, and why was it dubbed the "sexiest job of the twenty-first century" by the Harvard Business Review? Joining these free Data Science events will provide you with solutions to all of your frequently asked queries.

You may learn Data Science from the ground up by enrolling in one of these free online courses. They're also useful for filling in knowledge gaps if you're already undertaking data analysis, and the best part is that they're absolutely free.

List of Free Data Science Courses

1.       Introduction to AI and ML

2.       Python for Data Science

3.       Winning Data Science Competitions

4.       Regression

5.       Decision Trees

6.       Ensemble Learning

7.       Naive Bayes

8.       Evaluation Metrics

9.       Introduction to NLP

10.   Getting started with Neural Networks

11.   Loan Prediction Problem

 

1.     Introduction to AI and ML

Artificial Intelligence and Machine Learning have risen to the forefront of corporate strategic decision-making. They're changing the way industries and jobs work - from sales and marketing to finance and HR, businesses are relying heavily on AI and machine learning to gain a competitive advantage.

This, of course, has a direct impact on their hiring. Thousands of job openings exist as companies search the globe for AI and machine learning talent. There's never been a better moment to start working in this profession!

2.     Python for Data Science

Do you want to pursue a career in data science? Are you put off by the amount of coding you'll have to learn? Are you interested in learning Python in order to pursue a career in data science? You've arrived at the ideal location!

Python is a particularly versatile language because it comes with a large number of built-in features. Although the sheer number of functionalities may appear to be overwhelming and confusing, you do not need to be familiar with all of them.

1.       Python has quickly become the go-to language in the data science world, and it's one of the first skills employers look for in a data scientist.

2.       It constantly rates first in worldwide data science polls, and its mainstream acceptance will only grow in the future years.

3.       This language has developed a specific library for data analysis and predictive modelling over time, thanks to significant community support.

 

3.     Winning Data Science Competitions

 

Experience is the only thing that can replace it. And the same is true in Data Science competitions. To make it to the top of these cutthroat hackathons, you'll need a lot of trial and error, effort, and perseverance.

This course combines speeches from top data scientists and machine learning hackers, experts, practitioners, and leaders who have competed in and won dozens of hackathons.

There's a lot to learn from this course, from effective feature engineering to selecting the best validation approach, so get started now!

You can find the course material here.

4.     Regression

When developing machine learning models, the first Python package we use is Scikit-learn, or sklearn for short. Sklearn is by far the most popular Python package among data scientists. You should be familiar with sklearn and how to build ML models as a newbie to machine learning, including: 1. Linear Regression using sklearn

2. Sklearn Logistic Regression, and so forth.

Without a doubt, scikit-learn delivers useful tools with simple syntax. Scikit-learn (sklearn) is a prominent Python library that ranks among Pandas and NumPy in the top tier.

We appreciate scikit-clear, learn's consistent code and functionality. The superb documentation is the cherry on top, as it enables many beginners to develop machine learning models using sklearn on their own.

 In a nutshell, sklearn is a machine learning Python package that everyone should be familiar with. Sklearn is your go-to library for building linear regression and logistic regression models, decision trees, and random forests.

Sponsor Ads

• Ad Space Available - Rent it Now!

Created on Apr 8th 2022 06:09. Viewed 492 times.

Comments