A comprehensive intro to AI training course

Our AI training course for business and IT staff will introduce delegates to the possibilities offered by AI, as well as the terminology and market forces.

This is a short course to inspire and educate your business and IT community, to ensure that your organisation is well placed to take advantage of opportunities and to gain a competitive edge within the marketplace.

JBI's expert AI consultants will share real-world experiences and trends with delegates. This workshop can be brought onsite and run as a private course for your organisation, thus enabling a more open and relevant discussion to take place.

A comprehensive intro 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.

Machine Learning 

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

Automation in the workplace 

Maximising 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 visualisation 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 organisations 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.

Prerequisites

• Those attending this course should meet the following:
• Curiosity to learn about how AI systems work
• Some programming experience in any language like Python, R, Java
• Familiarity with basic mathematical and statistical concepts like algebra, probability
• Basic awareness of machine learning and artificial intelligence concepts through media, etc

                                                                                                                               FAQs - Introduction to AI Course

1. Introduction to AI

Q1: What is Artificial Intelligence (AI)?

 AI refers to the simulation of human intelligence in machines that are programmed to think and learn like humans.

Q2: What is the history of AI?

AI has its roots in the mid-20th century, with early developments in symbolic AI and the first AI programs. The field has evolved significantly since then, with milestones such as the development of expert systems and neural networks.

Q3: What are the differences between AI, Machine Learning, and Deep Learning?

AI is the broader concept of machines being able to carry out tasks in a way that we would consider "smart". Machine Learning is a subset of AI that focuses on the development of algorithms that enable computers to learn from data. Deep Learning is a subset of Machine Learning that uses neural networks with many layers to model and process data.

Q4: What are some real-world applications of AI?

AI is used in various industries and applications, including virtual personal assistants, recommendation systems, healthcare diagnostics, autonomous vehicles, and natural language processing.

Q5: What are the future perspectives on AI?

The future of AI holds immense potential for advancements in various fields, including healthcare, education, transportation, and entertainment. However, ethical and societal implications must also be carefully considered.

2. Basics of Machine Learning

Q6: What is Machine Learning?

Machine Learning is a subset of AI that enables machines to learn from data without being explicitly programmed.

Q7: What are the types of Machine Learning?

The main types of Machine Learning are Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

Q8: What are some real-world applications of Machine Learning?

Machine Learning is used in applications such as spam detection, image recognition, recommendation systems, and predictive analytics.