Courses

This is our beginner's course for coding with Python. All newbies are welcome! We cover Python basics such as installing Jupyter, working with strings, variables, arithmetic operations, conditional statements, etc.

Using Python for analytics but not sure how to showcase the results? This course has you covered! We explore libraries like matplotlib, seaborn, ggplot and bokeh to create stunning visuals in Python.

Let's build! A sequel to our introduction to PowerBI course, we focus on building intuitive, powerful reports and dashboards here. Many interesting features, hacks and best practices to use in PowerBI will be explored.

All you need to get started with data science is in this course! Beginners are welcome, but a background in Python programming is needed. If you need to brush up on Python, try our introduction to Python course.

This course is focused on introducing key data science concepts, data analytics basics and working with large scale datasets in Python.

This project based course will skip the theory and delve right into creating models. Familiarity with basics and terminology is needed so we recommend our introduction to data science course first if you're just starting out.

This is a beginner-friendly course for Microsoft PowerBI - the data visualization platform. We will include an overview, installation steps and background on PowerBI desktop as well as setting up of a PowerBI service account in this tutorial.

The succint PowerPoint slides will talk about various visuals and features of the tool while showcasing easy to understand examples. We will create a report using these visuals and learn how to import, transform and represent data.

This course will provide equip the learner with strong machine learning fundamentals. We will cover a wide array of fascinating use cases, real world problems and explore a variety of applications. This course is geared towards beginners and will go over basic terminology, Python libraries, basic ML algorithms and construction and use of machine learning models. At the end of the course, you will be able to effectively analyze data using ML and apply your knowledge to a final project to showcase your skills.