[UDM] Data Science Methods and Techniques Course (Feb 2025) + Resources

Learn Critical Data Science Skills
Find your niche in data science and be prepared to transform it with the Data Science Methods and Techniques Course, which aims to provide not only foundational experience but also new methods. The Data Science Methods and Techniques Course, developed by veteran teacher Henrik Johansson with over 20 years of teaching experience, will introduce you to the concepts and tools of regression, classification, and clustering, and progress to more advanced data analysis methods. If you are a beginner or need to refine your existing skills, the course offers a well-balanced combination of theoretical and practical activities that will reinforce your knowledge.

Upgrade Your Regression/ Classification Skills
You will immerse yourself in the world of regression techniques, beginning with the simplest of them, linear regression, and slowly, in stages, entering the world of multivariate regression and polynomial models. Algorithms, such as Random Forest and ensemble voting systems, are also discussed in depth in the Data Science Methods and Techniques Course as classification approaches. Through illustrative examples implemented in Python with the help of such libraries as scikit-learn, Statsmodels, Seaborn, and Matplotlib, you will learn how to use code to solve real-world problems.

Learn about Clustering and Unsupervised Learning, and AI Tools
Discover the potential of unsupervised learning using hierarchical clustering and the DBSCAN clustering algorithm. Intelligent model selection and automated AI-based prediction techniques are other aspects introduced in the course to assist you in developing an appreciation of how and when to apply the correct tool of the trade. The lessons are not just textbook knowledge, and they provide you with the capability of approaching complex data sets with ease and innovation.

Lab Practical with Python and Jupyter Notebooks
Exploring cloud-based notebooks and local development environments, you will be able to learn how to install and execute Python programs efficiently in Windows, macOS, Linux, or even a mobile system. Having got the instruction on the installation of Python, Pandas, and Anaconda, you will be able to analyze the data anywhere. Upon complete graduation, you would be in an ideal position to practice your data science expertise in academic studies, the workplace, or outside ventures.