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Data science can be a difficult endeavour
Data science can be difficult to understand. It is a field that spans a history of more than 100 years, and encapsulates artificial intelligence, machine learning, statistics and other disciplines that tried to solve the problem of extracting useful insights from data. Decision makers in small, medium and big enterprises are encountered with difficult technical dilemmas all the time. It doesn’t matter whether you are a CEO of a small company, a startup founder, a manager in a big corporation or a product manager, you will face questions such as :
- How can I use data science?
- How is technology X (e.g. Natural Language Processing, or deep learning).
- Should I go for commoditised services or develop machine learning capabilities in-house?
- How should I choose which data scientist to hire?
Decision makers rarely have the time to spend days educating themselves about a subject. What they need, is distilled information which will help them make informed decision as fast as possible. This is why through The Tesseract Academy I developed a seminar that teaches all the basics of data science in half a day. However, I realised, through the feedback of my clients, that they needed something to accompany the seminar. Something which would help solidify the knowledge.
The decision maker’s handbook to data science. Buy it on Amazon.
Decision Maker’s Handbook to Data Science
This is why I wrote the Decision Maker’s Handbook to Data Science. In the 142 pages of this book I outline topics such as:
- History of data science.
- Differences between AI, machine learning and statistics.
- Data management and building the right data strategy.
- Thinking like a data scientist (without being one).
- Hiring and managing data scientists.
- Building the right culture for data science.
Obviously, a book is not the same as an interactive session where we go through exercises and participants can ask questions. But it is the next best thing. The book always takes the perspective of the non-technical decision maker, making difficult concepts simple and explaining how they can be used in business in order to extract maximum value.