// 4 courses indexed
The course directory
Every course we track across 10+ providers, in one searchable index. Want a shortlist picked for your goals? Run a free skill gap analysis.
Python: Logistic Regression & Supervised ML
Build a strong foundation in supervised machine learning by learning how to develop, evaluate, and interpret classification models using Python. In this hands-on course, you will work with the real-world Titanic dataset to explore the complete machine learning workflow, from project setup and data preparation to model evaluation and deployment readiness. You will begin by understanding the lifecycle of a supervised machine learning project, defining problem objectives, and using essential Python libraries such as NumPy and pandas. You will also explore core supervised learning algorithms, inc
All levels
NumPy & Pandas: Analyze & Manage Retail Data
Build practical numerical computing and retail data analysis skills with NumPy and Pandas. Designed for aspiring data analysts, business intelligence professionals, and Python enthusiasts, this hands-on course guides you from NumPy foundations to advanced Pandas techniques through case studies and retail datasets. You’ll learn to create and manipulate NumPy arrays using slicing, reshaping, stacking, and broadcasting; apply linear algebra operations and implement gradient descent for analytical problems. You’ll then use Pandas to import data from multiple sources, clean and transform retail da
All levels
Data Structures in Python
In this course, you’ll explore data structures in Python, which are methods of storing and organizing data in a computer. You’ll focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You’ll also discover how to categorize data using data loading, cleaning, and binning. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas. By the end of this course, you will be able to: • Explain how to manipulate dataframes using techniques such as selecting and i
All levels
Data Science with NumPy, Sets, and Dictionaries
Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators. Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices. Hands-on practice with NumPy will equip you with essential skills to tackl
All levels