This spring become an IBM Certified Advanced Data Scientist for free
Announcing the new Applied AI Coder experience
IBM and Coursera are giving away subscriptions worth up to $1 million (U.S.) to help address the lack of skilled data scientists the world is currently facing. Similar to a scholarship, eligibility is independent on social status, location, gender and race. So in the spirit of having some fun – and to ensure highly motivated individuals (with a minimum set of prerequisite skills) are able to benefit most – we’ve created a technical challenge that focuses your learning and allows you to demonstrate your expertise…but please don’t worry, it’s not too hard!
In this challenge, we address data scientists wanting to get more practical experience. Come and learn the latest advancements in AI and deep learning, understand scalability, and get one month free subscription on Coursera for the most relevant courses.
How does it work?
- Access the IBM Developer community to Join the IBM Coder Program. You’ll be asked to create a profile, but it will only take a few minutes.
- Access the Applied AI Experience, start with the “Get Ready” challenge, and proceed with the subsequent challenges in the order they are presented.
As you complete the challenges, you’ll earn coins which advance you on the community leaderboard. Completing all 7 challenges will unlock a link to get the free Coursera subscription. If you’re already experienced, you’ll find the first challenges rather easy, but we want to ensure that everyone is on the same page in order to successfully complete the hands-on exercise at the end of the challenges.
You should be able to complete all challenges in less than 2-4 hours. Completing all the challenges and recommended learning material provides an important learning journey in itself. Ultimately, they’ll prepare you to solve a data science puzzle using real data from our Watson IoT Headquarters in Munich. Don’t worry, we provide the learning environment and a code skeleton for you, so you don’t have to worry about non-data science specific tasks.