Bio: Alex founded InnoArchiTech, a company focused on technical education, speaking, and writing. At his day job, Alex is the vice president of product and advanced analytics at Rocket Wagon, an enterprise IoT and digital services company. 

Alex is focused on leveraging artificial intelligence, machine learning, and data science to transform data into value for people and businesses, while also creating exceptionally designed, innovative products. 

Before working in tech, Alex spent ten years as a race strategist, vehicle dynamicist, and data scientist for IndyCar racing teams and the Indianapolis 500.

Objectives

• Provide an experienced guidance on Data Science projects.
• Share learned lessons
• Provide a general overview on the Data Science field

Timeline

• 0:40 – Introduction and presentation
• 1:24 – Studies and formation in fields of Data Science
• 3:35 – What can bring maths to the field of Data Science?
• 5:00 – What can bring software engineering to the field of Data Science?
• 6:02 – What is the best composition of a data science team?
• 7:54 – How a data scientist can split its time to learn new things
• 9:01 – How companies can start building a data science team
• 11:15 – What are the benefits of hackathons for data scientists?
• 12:14 – The curse of dimensionality in plain English
• 18:32 – What is your opinion on automated machine learning?
• 19:29 – How to approach new data science projects, from scratch.
• 21:29 – Strategies to turn failures into successful data science projects
• 23:23 – How data science will be in 5 to 10 years from now?
• 25:47 – How to start in the data science world
• 28:16 – How to deploy machine learning models in production
• 30:28 – Closing words

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