Data Science Seminar for Executives
Big Data, Data Science, Machine Learning, Artificial Intelligence, NLP and more.
What you will learn
This half-day intensive seminar for executives focuses on demystifying what Data Science is and its application and benefits in industry. Participants will get an overview of four key pillars: Big Data, Machine Learning, AI and Natural Language Processing through a mixture of case studies, practical demonstration and interactive exercises.
- 5Vs of Big Data
- Batch vs Stream processing
- Using Cloud technologies
- Practical Demo: Analysing big data data in 10min for less than the cost of a sandwich
Data Science and Machine Learning
- Why you should care and what is it?
- How to be smarter and more productive than Excel using Python
- Overview of the Machine Learning Pipeline: Train-test split, underfitting and overfitting Applications
- Practical: Train your own machine learning model in 10min using off-the shelf tools
- Deep Learning in a nutshell: how does it work?
- Case Studies: Self-driving cars and Energy consumption savings
Natural Language Processing
- Sentiment Analysis for company monitoring and intelligence collection
- The technology behind auto-summarising of news
- Case Studies: Analysing Trump’s tweets and summarising news
- Practical: Implementing a chatbot to automate customer interaction and support
The Future Evolution of Technology
- Insights from Facebook, Google and Amazon
- Impact of Data Science in the Finance Industry
- How to find and work with data scientists
- Get a technology edge
No prior programming experience required, this course is designed to equip you with an understanding of the basic concepts in data science.
Aimed at organization leaders, managers and business professionals from all sectors, this program will cover the fundamentals of Data Science and Big Data Analytics in Practice.
Get in Touch
CONTACT OUR ADMISSIONS TEAM
We will email you within the next 24 hours to arrange a quick call to help with any questions about the programme and recommend pre-course materials.