Seminar - Python, Data Analytics & AI to gain a competitive edge training course

Introduction to AI

• History of Artificial Intelligence - Once confined to the corridors of academia, AI is now having a massive impact on the world of business and beyond.
• Discover what changed in just the last 10 years, from the explosion of open source software to the big data revolution, to yield what The Economist now calls the fourth industrial revolution.

Introduction to ML

• Machine Learning - An overview of machine learning covering concepts, terminology and techniques along with case studies and examples.

Automation in the work place

• Maximizing impact from AI doesn't necessarily mean deploying self-aware intelligent systems.
• Currently a huge source of value is derived from simply automating complex processes, resulting in less busywork and increased productivity for employees.

A brief introduction to Big Data 

• What is Big Data, where did it come from, and a non-technical overview of common technologies used within the industry such as Hadoop and MapReduce.
• Chatbots, natural language processing and deep learning - A light summary of other related technologies within the field of Artificial Intelligence and their use cases within businesses.
• Tools for Data Scientists and non-Data Scientists - Overview of common tools for data munging, machine learning, data visualization and building dashboards.

Building your AI capability 

• Skills and traits of successful data scientists, how to build a data team, how to apply data science principles when hiring, and recommended resources for individual skill development.

Opportunities for businesses 

• Where are the opportunities for organizations looking to invest in data initiatives, the challenges inherent in building a data-driven culture, and solutions with case studies.

The future of the workplace 

• A look at industry trends and what the future may bring.