70 Free Online Courses for Data Science to Advance Your Skills in 2024

70 Free Online Courses for Data Science to Advance Your Skills in 2024

Data Science / By Aqsa Zafar / June 25, 2024

 

 

https://www.mltut.com/free-online-courses-for-data-science/?fbclid=IwY2xjawG-jelleHRuA2FlbQIxMAABHUbXBni6jLdfrp30kxqAvyZtWsI3roQiqKNy1j2gUI1eL_kvVslflUfW5w_aem_DvkXyIeCkzAUEPnOtPM7Ow

Are you looking for Free Online Courses for Data Science? If yes, then this article will help you and provide 70 free online courses for Data Science from various platforms. So give your few minutes and find out the best free data science online course for you.

I would recommend you bookmark this article for future reference. Because this article will not only provide free courses but also saves your searching time for different free data science courses.

NOTE- The courses which I have listed in this article are completely free. You don’t need to pay a single buck for the course.

So without any further ado, let’s get started-

Free Online Courses for Data Science

For your convenience, I have created a table, so that you can filter out the courses according to your need. But before discussing the courses, I would like to tell you the required data science skills.

A data scientist requires an in-depth knowledge of the following skills-

1. Programming Skills
2. Statistics or Probability
3. Machine Learning
4. Multivariate Calculus and Linear Algebra
5. Data wrangling.
6. Data Visualization.
7. Database Management
8. BigData

Now let’s get started and find out free online courses for Data Science.

S/N	Course Name	Rating	Provider	Time to Complete	Level
1.	Intro to Data Science	4.7/5	Udacity	2 Months	Intermediate
2.	Foundations of Data Science: K-Means Clustering in Python	4.6/5	Coursera	29 hours	Beginner
3.	Data Science in Stratified Healthcare and Precision Medicine	4.6/5	Coursera	17 hours	Intermediate
4.	Bayesian Statistics: From Concept to Data Analysis	4.6/5	Coursera	12 hours	Intermediate
5.	Data Analysis and Visualization	4.7/5	Udacity	16 Weeks	Intermediate
6.	Data Visualization and D3.js	4.7/5	Udacity	7 Weeks	Intermediate
7.	Data Analysis with R	4.6/5	Udacity	2 Months	Intermediate
8.	Spark	4.5/5	Udacity	10 Hours	Intermediate
9.	Essentials of Data Science	4.4/5	Udemy	1hr 41min	Beginner
10.	R Basics – R Programming Language Introduction	4.5/5	Udemy	4hr 6min	Beginner
11.	Data Wrangling with MongoDB	4.7/5	Udacity	2 Months	Intermediate
12.	Statistics	4.7/5	Udacity	4 Months	Beginner
13.	Intro to Data Analysis	4.6/5	Udacity	6 Weeks	Beginner
14.	Model Building and Validation	4.7/5	Udacity	8 Weeks	Advanced
15.	Machine Learning by Stanford University	4.9/5	Coursera	60 hours	Beginner
16.	Process Mining: Data science in Action	4.8/5	Coursera	22 hours	Intermediate
17.	Data Analytics for Lean Six Sigma	4.8/5	Coursera	11 hours	Beginner
18.	Probability and Statistics	4.6/5	Coursera	16 hours	Beginner
19.	Data Science Ethics	4.8/5	Coursera	15 hours	Beginner
20.	An Intuitive Introduction to Probability	4.7/5	Coursera	30 hours	Beginner
21.	Practical Time Series Analysis	4.6/5	Coursera	26 hours	Intermediate
22.	Real-Time Analytics with Apache Storm	4.7/5	Udacity	2 Weeks	Intermediate
23.	Linear Algebra Refresher Course with Python	4.7/5	Udacity	4 Months	Intermediate
24.	Improving your statistical inferences	4.9/5	Coursera	28 hours	Intermediate
25.	Hands-on Text Mining and Analytics	3.9/5	Coursera	13 hours	Intermediate
26.	Improving Your Statistical Questions	4.9/5	Coursera	18 hours	Intermediate
27.	Population Health: Predictive Analytics	5.0/5	Coursera	18 hours	Intermediate
28.	Introduction to Data Science using Python (Module 1/3)	4.4/5	Udemy	2hr 32min	Beginner
29.	What is Data Science?	4.2/5	Udemy	40min	Beginner
30.	Python For Data Science	4.4/5	Udemy	3hr 55min	Beginner
31.	Learn NumPy Fundamentals (Python Library for Data Science)	4.6/5	Udemy	1hr 49min	Beginner
32.	Python for Data Science – Great Learning	4.2/5	Udemy	1hr 55min	Beginner
33.	Intro to Data for Data Science	4.4/5	Udemy	1hr 1min	Beginner
34.	Data Science, Machine Learning, Data Analysis, Python & R	3.9/5	Udemy	8hr 7min	Beginner
35.	Python Crash Course for Data Science and Machine Learning	4.6/5	Udemy	1hr 39min	Beginner
36.	Data Science with Analogies, Algorithms, and Solved Problems	4.0/5	Udemy	1hr 19min	Beginner
37.	Learn Data Science With R	4.4/5	Udemy	8hr 42min	Beginner
38.	Introduction to Python For Data Science 2024	4.3/5	Udemy	57min	Beginner
39.	NumPy for Data Science Beginners: 2024	4.3/5	Udemy	1hr 51min	Beginner
40.	Data Science for Business Leaders: Machine Learning Defined	4.3/5	Udemy	1hr 58min	Beginner
41.	An Athlete’s Guide To Data Science	4.3/5	Udemy	1hr 1min	Beginner
42.	A – Z™ Python crash course for Data Science 2024	4.1/4	Udemy	2hr	Beginner
43.	How To Build a Career in Data Analytics and Data Science	4.3/5	Udemy	1hr 39min	Beginner
44.	Data Science – Data Mining Unsupervised Learning R & Python	4.5/5	Udemy	1hr 52min	Beginner
45.	Data Analysis with Python	4.6/5	Udemy	1hr 19min	Intermediate
46.	Data Visualization	NA	Kaggle	4 hrs	Beginner
47.	Pandas	NA	Kaggle	4 hrs	Beginner
48.	Data Cleaning	NA	Kaggle	4 hrs	Intermediate
49.	Feature Engineering	NA	Kaggle	6 hrs	Intermediate
50.	Explore, Track, Predict the ISS in Realtime With Python	4.5/5	Udemy	1hr 13min	Intermediate
51.	SQL Crash Course for Aspiring Data Scientist	4.1/5	Udemy	1hr 24min	Beginner
52.	SQL for Data Analysis: Solving real-world problems with data	4.4/5	Udemy	1hr 57min	Beginner
53.	Introduction to Data Science	NA	edX	6 Weeks	Beginner
54.	Data Science Tools	NA	edX	7 Weeks	Beginner
55.	The Math of Data Science: Linear Algebra	NA	edX	8 Weeks	Intermediate
56.	Data Science: R Basics	NA	edX	8 Weeks	Beginner
57.	Python Basics for Data Science	NA	edX	5 Weeks	Beginner
58.	Data Science: Visualization	NA	edX	8 Weeks	Beginner
59.	SQL for Data Science	NA	edX	8 Weeks	Beginner
60.	Statistical Thinking for Data Science and Analytics	NA	edX	5 Weeks	Beginner
61.	Data Science: Machine Learning by HarvardX	NA	edX	8 Weeks	Beginner
62.	Machine Learning Crash Course	NA	Google	15 hours	Beginner
63.	Learning from Data	NA	Caltech	18 hours	Intermediate
64.	Data Science Full Program by Edureka	NA	YouTube	10 hours	Beginner
65.	Data Science Tutorial by Great Learning	NA	YouTube	11 hours	Beginner
66.	Data Science Full Course For Beginners	NA	YouTube	NA	Beginner
67.	Learn Data Science Tutorial – Full Course for Beginners	NA	YouTube	6 hours	Beginner
68.	Data Science Full Course by Simplilearn	NA	YouTube	10 hours	Beginner
69.	Python for Data Science	NA	YouTube	12 hours	Beginner
70.	Statistics and Probability Full Course	NA	YouTube	11 hours	Beginner

And here we go!

Now, let’s see 10 beginner-friendly data science projects-

10 Beginner-Friendly Data Science Projects-

1. Fake News Detection

There is a lot of fake news spreading all over the world. So how can we differentiate between true news and false news?… The answer is with the help of Python. In this project, you have to build a model by using the Python programming language, which can identify whether the news is true or fake.

In order to implement this project, you need to build a TfidfVectorizer and use a PassiveAggressiveClassifier to classify news into “Real” and “Fake”. 

You can check the tutorial for this project in Datacamp and in DataFlair.

2. Build a Chatbots

When you have any query with any product, then you complain to customer support. So when you send a message with your query, you get a reply within a few seconds. So this is a Customer Support Bot, that understands your language by processing and then replies to your query.

You can check examples of chatbots in eCommerce, healthcare, entertainment, and customer service in this article- The Best Chatbot Examples and Awesome Chatbot Ideas That You Can Borrow.

You can check this tutorial to build your first chatbot from scratch- Build Your First Python Chatbot Project

3. Recommendation System

As a beginner in machine learning, you can start your first project as a Recommendation system. Where you have to build a system that will recommend the products based on user history. Something like Amazon or Netflix.

You can build a Music recommendation system, movie recommendation system, etc.

For the recommender system datasets, you can refer to the UCSD portal. In this portal, you will find some rich datasets that were used in lab research projects at UCSD.

This portal has various datasets available for recommender systems from popular websites like Goodreads book reviews, Amazon product reviews, bartending data, etc.

Portal Link- Recommender Systems Datasets

And you can also check this complete project on Movie Recommendation System in R.

4. Driver Drowsiness Detection

Road Accident is a serious problem and the major reason is the sleepy drivers. But you can prevent this problem by creating a driver drowsiness detection system.

Driver Drowsiness Detection system detects the drowsiness of the driver by constantly assessing the driver’s eyes and alerting him with alarms.

For this project, a webcam is necessary to monitor the driver’s eyes. Python, OpenCV, and Keras are used to alert the driver when he feels sleepy.

You can check this complete project tutorial here- Driver Drowsiness Detection System with OpenCV & Keras.

5. Sentiment Analysis 

In natural language processing, sentiment analysis is used to interpret the sentiments and classify them as positive, negative, and neutral.

Sentiment analysis is used in various domains, especially in business. Businesses are using sentiment analysis to find the opinions of their customers by using customer reviews to improve their services.

Many Political parties are using sentiment analysis to plan their election campaigns. So if you want to implement sentiment analysis, you can find the datasets from these websites-

Datasets For Sentiment Analysis–

1. Twitter US Airline Sentiment– Kaggle
2. Paper Reviews Data Set– UCI
3. Sentiment Lexicons for 81 Languages– Kaggle
4. Amazon product data
5. Stanford Sentiment Treebank

You can also check this tutorial for the Sentiment Analysis Project in R.

6. Credit Card Fraud Detection Project

In this project, you have to perform the detection of credit cards by using R programming and algorithms like Decision Trees, Logistic Regression, Artificial Neural Networks, and Gradient Boosting classifiers.

You will use the Card Transactions dataset to classify credit card transactions into fraudulent and genuine. And you will apply different machine learning algorithms and check the accuracy by plotting the performance curves.

You can check this Project Tutorial at DataFlair.

7. Road Lane line detection

This is another good project idea for data science beginners. This project will provide guidance to human drivers on lane detections through lines drawn on the road.

This project is done using the concepts of computer vision using the OpenCV library. For detecting the lane, you have to detect the white markings on both sides of the lane. And for this, frame masking is used.

You can download the source code of the project here.

8. Color Detection with Python

This is a beginner-level project, where you have to build an interactive app. This app will identify the selected color from any image. There are 16 million colors based on the different RGB color values, but we only know a few colors.

So to implement this project, you need to have a labeled dataset of all the colors that we know, and then you need to calculate which color resembles the most with the selected color value.

In order to implement this project, you should be familiar with Computer Vision Python libraries- OpenCV and Pandas.

You can check all the details regarding this project here.

9. Stock Price Predictor

This is another Best machine learning project for beginners. Various companies and businesses are looking for software that can monitor and analyze the company’s performance and predict future prices of various stocks.

As a beginner, you can develop a machine learning project that predicts the stock price for the upcoming months.

You can check this tutorial for Stock Price Prediction in Python. In this tutorial, you will learn how to predict stock prices using the LSTM neural network. And how to build a dashboard using Plotly dash for stock analysis.

10. Forest Fire Prediction

Forest Fire is one of the most common disasters in today’s world. Forest Fire damages our ecosystem. Forest fire is also a severe enemy of animals.

So, you can build a Forest fire prediction system using k-means clustering. The forest fire prediction system identifies major fire hotspots and their severity. 

You can also use meteorological data for finding the common seasons for wildfires and various weather conditions to increase your model’s accuracy.

You can check this tutorial for Forest Fire prediction here.

So, these are the 10 Projects for Data Science Beginners.

FAQ on FREE Data Science Courses

How can I learn data science for free?

How can I become a data scientist from scratch free?

Is IBM Data Science Coursera free?

That’s all.

Conclusion

So, these are the 70 Best Free Online Courses for Data Science in 2024. I will keep adding more free courses to this list.

But I hope these Free Online Courses for Data Science will help you to enhance your data science skills. If you have any doubt or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

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Thank YOU!

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Though of the Day…

‘ It’s what you learn after you know it all that counts.’

– John Wooden