Highlights
AI Foundation Training:
- Introduction to AI
- History of Artificial Intelligence
- Basics of Machine Learning
- Automation in the workplace
- A brief introduction to Big Data
- Introduction to Deep Learning
- Building your AI capability
- Opportunities for businesses
- The future of the workplace
- Tools for Data Scientists and non-Data Scientists
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Chatbots, natural language processing and deep learning
Course Details
History of Artificial Intelligence:
- Explore the evolution of AI from its academic beginnings.
- Understand the impact of the last decade’s technological advancements.
- Learn about the key milestones that have driven the AI revolution.
Machine Learning:
- Gain an overview of essential machine learning concepts and terminology.
- Discover various machine learning techniques through case studies.
- See practical examples of machine learning applications.
Automation in the Workplace:
- Learn how AI-driven automation can maximize business impact.
- Explore real-world examples of process automation reducing busywork.
- Understand how automation boosts productivity and efficiency.
A Brief Introduction to Big Data:
- Understand the origins and significance of Big Data.
- Get a non-technical overview of industry-standard technologies like Hadoop and MapReduce.
- Discover how Big Data is leveraged in various industries.
Chatbots, Natural Language Processing, and Deep Learning:
- Dive into the world of chatbots and their business applications.
- Explore natural language processing and its impact on AI communication.
- Learn about deep learning and its transformative potential.
Tools for Data Scientists and Non-Data Scientists:
- Get introduced to essential tools for data analysis and visualization.
- Learn about tools for machine learning and building dashboards.
- Understand the resources available for both technical and non-technical users.
Building Your AI Capability:
- Identify the skills and traits of successful data scientists.
- Learn how to build and manage a data team.
- Discover resources for individual skill development and continuous learning.
Opportunities for Businesses:
- Explore the opportunities for organizations investing in AI and data initiatives.
- Understand the challenges in building a data-driven culture.
- Learn from case studies showcasing successful AI implementations.
The Future of the Workplace:
- Examine industry trends shaping the future of work.
- Understand the potential future developments in AI and machine learning.
- Explore predictions and insights into the evolving workplace dynamics.
Conclusion: Prepare yourself and your business for the AI-driven future. This comprehensive course will equip you with the knowledge and tools to leverage AI effectively and stay ahead in the rapidly evolving landscape.
Who should attend
This course is ideal for business leaders, managers, and professionals who want to understand the potential of AI and its impact on their industry. It’s also suited for data scientists, IT professionals, and anyone responsible for driving innovation or leading digital transformation initiatives within their organization.
Whether you're new to AI or looking to expand your knowledge, this course provides valuable insights and practical tools to help you harness AI’s capabilities and prepare your team for the future. Those interested in staying ahead in the rapidly evolving world of technology and data analytics will find this course particularly beneficial.
Feedback
4.8 out of 5 average
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”
Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022
