Data Science and Machine Learning Fundamentals [2025]

Learn to master Data Science and Machine Learning Fundamentals with Python and Pandas

4.90 (641 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Knowledge about Data Science and Machine Learning theory, algorithms, methods, best practices, and tasks

Deep hands-on knowledge about Data Science and Machine Learning, and know how to do common Data Science and Machine Learning tasks

The ability to handle common Data Science and Machine Learning tasks with confidence

Master Python for Data Handling

Master Pandas for Data Handling

Knowledge and practical hands-on knowledge of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and many other Python libraries

Detailed and deep, Master knowledge of Regression, Regression Analysis, Prediction, Classification, and Cluster analysis

Advanced knowledge of A.I. prediction models and automatic model creation

Advanced Knowledge of Text Mining, Text Mining Tasks, and Emotion Mining

Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources

Course Gallery

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Data Science and Machine Learning Fundamentals [2025] – Screenshot 4 — Screenshot 4 – Data Science and Machine Learning Fundamentals [2025]

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Comidoc Review

Our Verdict

TheData Science and Machine Learning Fundamentals [2025] course presents a compelling opportunity for learners to gain extensive knowledge, excel in Python data handling, and develop hands-on expertise utilizing an assortment of essential libraries. While occasionally challenging due to its vast material, the engaging presentation style and thorough foundational approach cater effectively to diverse learning needs.

What We Liked

Comprehensive coverage of Data Science and Machine Learning Fundamentals using Python and Pandas, ideal for both beginners and those looking to enhance their skills
In-depth exploration of Scikit-learn, Statsmodels, Matplotlib, Seaborn, and other Python libraries, enabling mastery in data handling and visualization
Expert presentation of Regression, Classification, and Cluster analysis, providing strong knowledge and practical implementation skills
Structured curriculum with clear, engaging explanations and careful pacing to ensure thorough understanding

Potential Drawbacks

Absence of prepared code documentation may lengthen the learning process for some students who wish to copy-paste sections of code during practice
The sheer scope and depth of topics covered can be overwhelming, particularly for those new to Data Science and Machine Learning concepts
Presentation contains minor inconsistencies in color scheme and slides design that may appear unpolished to some users
Several sections could benefit from further updating with the most recent API changes