Data Science Methods and Algorithms [2026] (Udemy.com)
Learn Data Science Methods and Algorithms with Pandas and Python [2026]
Created by: Henrik Johansson
Last updated September 2026
What you will learn
- Knowledge about Data Science methods, algorithms, theory, best practices, and tasks
- Deep hands-on knowledge of Data Science and know how to handle common Data Science tasks with confidence
- Detailed and deep Master knowledge of Regression, Prediction, Classification, Supervised Learning, Cluster Analysis, and Unsupervised Learning
- Hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and some other Python libraries
- Advanced knowledge of A.I. prediction models and automatic model creation
- Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
- Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
- Master the Python 3 programming language for Data Handling
- Master Pandas 2 and 3 for Advanced Data Handling
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.7 out of 5higher than 85% of them
- Reviews1,127#142 of 462 by number of reviews
- Length51.4 hourslonger than 95% of them
- Last updatedSeptember 2026more recently than 90% of them
Course Description
Welcome to the course Data Science Methods and Algorithms with Pandas and Python!
Data Science is expanding and developing on a massive and global scale. Everywhere in society, there is a movement to implement and use Data Science Methods and Algorithms to develop and optimize all aspects of our lives, businesses, societies, governments, and states.
This course will teach you a large selection of Data Science methods and algorithms, which will give you an excellent foundation for Data Science jobs and studies. This course has exclusive content that will teach you many new things regardless of if you are a beginner or an experienced Data Scientist.
This is a five-in-one master class video course which will teach you to master Regression, Prediction, Classification, Supervised Learning, Cluster analysis, Unsupervised Learning, Python 3, Pandas 2 + 3, and advanced Data Handling.
You will learn to master Regression, Regression analysis, Prediction and supervised learning. This course has the most complete and fundamental master-level regression content packages on Udemy, with hands-on, useful practical theory, and also automatic Machine Learning algorithms for model building, feature selection, and artificial intelligence. You will learn about models ranging from linear regression models to advanced multivariate polynomial regression models.
You will learn to master Classification and supervised learning. You will learn about the classification process, classification theory, and visualizations as well as some useful classifier models, including the very powerful Random Forest Classifiers Ensembles and Voting Classifier Ensembles.
You will learn to master Cluster Analysis and unsupervised learning. This part of the course is about unsupervised learning, cluster theory, artificial intelligence, explorative data analysis, and some useful Machine Learning clustering algorithms ranging from hierarchical cluster models to density-based cluster models.
You will learn to master the Python 3 programming language, which is one of the most popular and useful programming languages in the world, and you will learn to use it for Data Handling.
You will learn to master the Pandas 2 and future 3 library and to use Pandas powerful Data Handling techniques for advanced Data Handling tasks. The Pandas library is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation tool, which is directly usable with the Python programming language, and combined creates the world’s most powerful coding environment for Data Handling and Advanced Data Handling…
You will learn
Knowledge about Data Science methods, algorithms, theory, best practices, and tasks
Deep hands-on knowledge of Data Science and know how to handle common Data Science tasks with confidence
Detailed and deep Master knowledge of Regression, Regression analysis, Prediction, Classification, Supervised Learning, Cluster Analysis, and Unsupervised Learning
Hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and some other Python libraries
Advanced knowledge of A.I. prediction models and automatic model creation
Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life
Master the Python 3 programming language for Data Handling
Master Pandas 2 and 3 for Advanced Data Handling
And much more…
This course includes
a comprehensive and easy-to-follow teaching package for Mastering Python and Pandas for Data Handling, which makes anyone able to learn the course contents regardless of beforehand knowledge of programming, tabulation software, Python, Data Science, or Machine Learning
an easy-to-follow guide for using the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). You may learn to use Cloud Computing resources in this course
an easy-to-follow optional guide for downloading, installing, and setting up the Anaconda Distribution, which makes anyone able to install a Python Data Science environment useful for this course or for any Data Science or coding task
content that will teach you many new things, regardless of if you are a beginner or an experienced Data Scientist
a large collection of unique content, and this course will teach you many new things that only can be learned from this course on Udemy
A course structure built on a proven and professional framework for learning.
A compact course structure and no killing time
This course is an excellent way to learn to master Regression, Prediction, Classification, Cluster analysis, Python, Pandas and Data Handling! These are the most important and useful tools for modeling, AI, and forecasting. Data Handling is the process of making data useful and usable for regression, prediction, classification, cluster analysis, and data analysis.
Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks. Being good at Python, Pandas, and Data Handling are extremely useful and time-saving skills that functions as a force multiplier for productivity.
Is this course for you?
This course is for you, regardless if you are a beginner or an experienced Data Scientist
This course is for you, regardless if you have a Ph.D. or no education or experience at all
This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Regression, Prediction, Python, Pandas, and Data Handling.
Course requirements
The four ways of counting (+-*/)
Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
Access to a computer with an internet connection
Programming experience is not needed and you will be taught everything you need
The course only uses costless software
Instructor Details
- 4.7 Rating
1,127 Reviews
Henrik Johansson
Henrik has a wide instructor/lecturer experience with more than 20 years in roles ranging from University teacher to sports coach to leadership roles in the private and public sectors.
Henrik has experience teaching students from all walks of life, from the poor to royalty, and has taught students from nearly all educational backgrounds, from high school to Ph.D.s.
Courses given by Henrik are intended to have unique content, and will teach you many new things.
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Reviews
By Lim Wang on 2/21/2026
Henrik is a great instructor! I have studied data science and decision theory for some years, and this course gave me incredible understanding - suddenly I understand everything, can do stuff, and most things has become very easy!
By Adam R. Curtis on 1/20/2026
Great, well-structured course, useful content, megabytes of ML code. The professor speaks with a clear, confident, and easy-to-understand voice. The videos are edited with almost no disturbances and useful edited captions. I recommend this course!
By Chocolate on 1/19/2026
kinda hard to listen
By Amber Green on 8/23/2025
I enjoyed this course and its combination of width and depth. Two thing that made me very happy is the resources and focus on making data science for real without any hard to understand hieroglyphs, or near impossible obstacles to create the shown data science for real.
By Wilhelmina Busch on 7/17/2025
Wow, this course is amazing and eye-opening. The course is well designed, living, updated, and is about practical and useful data science. I recommend this course!
By Michelle Rodriguez on 7/13/2025
The course is a very thorough and practical data science course. It has a very serious instructor and is very organized. I recommend this course to anyone who wants to learn to use data science for real or sharpen their data science skills!
By Justin McCuller on 6/4/2025
I really think it's worth the value now. However, I would have appreciated the inclusion of more hands-on resources, such as applied projects or case studies, beyond simply following along, copying, and looking at his code. That said, the course delivers a substantial amount of information on the underlying methodologies of Data Science, offering a solid conceptual foundation.
By Cyril D. Carpentier on 2/22/2025
This course is a excellent course. Anyone who wants to learn almost everything about data science methods and algorithms should begin wit this course. The instructor is clear-voiced and gives a comprehensive big-sized course with lots or resources.
By Sandra M. on 7/17/2024
It is a great and useful set of videos, that covers a large number of data science and machine learning methods, algorithms, and uses. Useful and worth your time.
By Wayne Davidsson on 6/24/2024
The course covers a lot of interesting topics for data scientist, programmer, or computer science person. It makes you feel like you can use a large number of methods and teaches you analysis in a new different way. I recommend the course!
Quality Score
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Overall Score : 94 / 100
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