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Quite often, students who start learning Data Science as a subject matter, start with learning the basic concepts of programming language such as Python, or R – and they think they will never finish up as they don’t seem to build confidence in learning the language.

While this bottom-up approach is not an incorrect approach for many who can quickly climb up the ladder of learning Python language, most often I’ve found most students stuck in the infinite learning loop of tutorials – to which some bloggers have even called a ‘Tutorial Hell’   – from which they never come out – or they don’t know when to stop and switch over to a higher hierarchy of learning, so they can get benefits of actually making a project or a product, or get their desired job.

At Devniti, we start with a balance of bottom-up and top-down approaches in learning so that the students make a sense of the end goal where their efforts are directed. While we introduce the basic concepts of Python and fundamentals of data science machine learning, right within first week of learning, we also start introducing our trainees with a live or capstone Data Science project so as to give them a sense of direction and sharpen their learning curve.  The idea is to apply what you learned – to create a practical outcome.

Looking at the complete project, they get a full picture of how the low level detailed tasks of learning coding snippets delve into a full fled Machine Learning algorithm to deliver the predictions in a Data Science project.

While there is no hard coded way to learn things, the adoption of top-down approach along with hands-on bottom-up approach has come to us as a proven way to get more successful and fruitful training completions.