What you'll learn,
video by video.
Sundas opens the course by sharing the exact mindset shift that changed everything for her. You'll understand why most self-taught learners stay stuck — and how to think differently from the first week. This is not a motivational talk. It's a practical reframe about what "ready" actually means, what self-taught professionals get wrong, and how to build momentum without a clear starting point.
Sundas breaks down the four core skills that hiring managers at Amazon and Google actually care about: Python, SQL, statistics, and data storytelling. She explains exactly what level you need to reach in each, what order to learn them in, and which topics you can safely skip. This part alone will save you months of wasted study time.
Sundas walks through what her own portfolio looked like when she was applying for her first data science role at Amazon. She shows you the types of projects that matter, the ones that don't, and how to frame your work so it reads as professional experience even before you have any. You'll leave knowing exactly what to build and how to present it.
Most people apply to 50 jobs and hear nothing. Sundas explains why that happens — and what to do instead. She covers how to structure your CV for maximum recruiter impact, which keywords matter, and how to build a targeted application strategy using LinkedIn, warm outreach, and cold email. Fewer applications, better results.
Sundas demystifies the data science interview process from both sides of the table. She covers the types of questions you'll face across technical rounds, SQL assessments, and case study exercises, and explains how she personally prepared when she had no prior data science experience to draw on. This is how to interview with confidence before you feel ready.
