Course Content
Frequently Asked Questions
Do I have to have knowledge in Statistics?
Though having knowledge in statistics may help you understand the concepts, it is not necessary to have in-depth knowledge to join the course. The statistics fundamentals and core concepts required for Machine Learning will be taught as part of this course. Remember, our focus is data science, not statistics, though data science requires statistics knowledge.
In which language is this course be taught?
The course will be taught using Python as Python is the most popular and widely used language for Data Science.
Is the course a hands-on one?
Yes, this course is mostly hands-on. However, slide decks are used to explain the core concepts and statistics.
I do have minimal program experience. Can I still take this course?
Though data science relies on programming, it is not necessary that you should be very experienced in programming. As programming will also be taught as part of this course, it should be easy to pick-up the knowledge/experience. However, during and after the course, we would highly recommend you spend a few more extra hours every day honing your knowledge.
What are the core concepts covered in this course?
This course focuses on Supervised and Unsupervised learning. Function, Instance, Probability, and Tree-based algorithms will be used for the Machine Learning part.
Are there any other concepts covered as part of this course?
Hyper-parameter tuning, model ensemble, and model stacking are covered as part of this course. This course gives an introduction to Neural Network as well.
Does this course cover the implementation of a Machine Learning model in production?
Yes. As part of this course, you will generate a Machine learning model, expose it as a service using the Flask micro-services framework, and implement it using the Heroku platform.
Is there any real-time dataset used in this course?
Yes, the real-time dataset hosted by the University of California at Irvine (UCI) library will be used throughout the course.
Are there Titanic and Iris datasets used in this course?
No, the datasets used will be from UCI's library.
What if I miss a session/class?
All the classes are recorded through-out. At the end of the class, the recorded session will be uploaded on the Slack channel. You are suggested to download the recording from Slack and watch it before the next session.
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