Learn Data Science
16 expert-rated courses covering Data Science. Compared by rating, price, difficulty, and job relevance so you can pick the right one.
The SkillsetCourse catalog offers a robust selection of 26 Data Science courses across platforms like IBM Skills Network, Udemy, and Coursera. There are 4 free options and 12 courses that provide certificates upon completion. This diversity allows learners to tailor their education to specific interests and career goals, with related skills such as Data Analysis and Deep Learning enhancing their knowledge base.
Catalog analysis updated . Ratings are independent editorial scores. Read the rating methodology.
Key Facts About Data Science
- 1Data Science integrates statistics, programming, and domain knowledge to derive insights from data.
- 2SkillsetCourse offers 26 Data Science courses across multiple platforms for diverse learning experiences.
- 312 courses in the catalog provide certificates, validating learners' skills and knowledge.
- 4Free options are available, making Data Science accessible to a broader audience.
- 5Related skills like Python and Machine Learning are essential for success in Data Science.
Top Data Science Courses
The Machine Learning Lifecycle: From Data Ingestion to Responsible Deployment
Learn the complete machine learning lifecycle from initial data ingestion through to responsible deployment in production. This course covers best practices for building, validating, and deploying ML models while considering ethical implications and responsible AI practices.
IBM Data Science Professional Certificate
Comprehensive data science program by IBM. Learn Python, SQL, data analysis, machine learning, and data visualization.
IBM Certified Data Scientist Watson Practice Exams
Practice exams designed to prepare you for IBM Certified Data Scientist certification. Test your knowledge of AI, machine learning, and data science concepts using IBM Watson technologies.
Machine Learning with Python
Learn machine learning using Python, the industry-standard language for data science and AI. Work with popular libraries like scikit-learn, TensorFlow, and pandas to build practical ML models. Ideal for intermediate programmers wanting to enter the machine learning field.
Python for Applied Data Science & AI
Master Python programming for data science and AI applications with practical examples and projects. Learn essential libraries like NumPy, pandas, and scikit-learn for data manipulation and analysis. Perfect foundation for anyone entering the data science or AI field.
Data Science and Machine Learning with Python
By the end of this class, you will not only have a solid understanding of data science and analytics but also be able to quickly learn new libraries and tools.
Pandas for Data Analysis: Master Data Handling in Python
This course covers everything from setting up your working environment with Anaconda and Jupyter Notebook to mastering the core features of Pandas.
Excel to Python: A Data Science Crash Course
Introduction: Do you do data science with Excel and then Python? And welcome to a Skillshare crash course where you will learn the fundamentals of Python for ...
Data Visualization with Matplotlib: From Basics to Advanced ...
In this course, you'll master data visualization using Matplotlib, one of the most powerful libraries in Python.
Machine Learning with Python and Scikit-learn for absolute beginners
This course covers how to build Machine Learning models from scratch using Python and Scikit-learn libraries. Course structure is captured below.
Python For Beginners: Master the Essential Basics of Python
By learning Python, you're preparing yourself for a future in: Data Science and Analytics: Process, analyze, and visualize data to make smarter decisions.
The No-Code Data Science Masterclass for Business Analysts ...
We will cover the expectations, steps, and vocabulary needed to make data-driven decisions. This class is tool-agnostic and can be applied in multiple contexts ...
SQL for Data Science
Learn SQL programming for data analysis and manipulation in data science workflows. Master database queries, joins, aggregations, and data wrangling techniques for extracting insights from relational databases.
Overfitting and Underfitting: Avoiding Model Pitfalls
Learn to identify and prevent overfitting and underfitting in machine learning models. This course covers techniques to optimize model performance and avoid common pitfalls in model development.
Introduction to Machine Learning
A foundational course covering the core concepts and algorithms of machine learning. Students will learn supervised and unsupervised learning techniques, model evaluation, and practical applications.
Traditional AI and Machine Learning Online Training Courses
A comprehensive collection of online training courses covering traditional AI and machine learning topics. Explore algorithms, model development, and practical implementations across multiple learning paths.
Pro Tips for Learning Data Science
- #1Start with foundational courses like 'Python for Applied Data Science & AI' to build essential programming skills.
- #2Engage in hands-on projects to apply theoretical knowledge and gain practical experience in Data Science.
- #3Utilize free resources to explore various aspects of Data Science before committing to paid courses.
- #4Join online communities or forums to network with other learners and professionals in the Data Science field.
Why Learn Data Science?
- Learning Data Science can lead to career advancement in tech, finance, healthcare, and other sectors.
- Data Science skills are increasingly in demand, enabling professionals to make data-driven decisions.
- Acquiring Data Science knowledge can enhance problem-solving abilities and analytical thinking.
- Data Science provides opportunities to work on innovative projects involving AI and machine learning.
AI Tools for Data Science
Apply your Data Science skills with these recommended tools: