Introduction to Data, AI, and Machine Learning Training
Training Objectives
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Foundation Building: Provide participants with a solid understanding of the concepts of data, artificial intelligence (AI), and machine learning (ML).
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Practical Insights: Offer real-world examples and applications to illustrate how data, AI, and ML are transforming industries.
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Empower Decision-Making: Equip participants with the knowledge to make informed decisions related to data-driven strategies and AI integration.
Training Duration: 1 day session
Training Fee: €1500
Module 1: Understanding Data in the Modern World (1 hour)
- Introduction to Data: Defining data and its significance in various contexts.
- Data Types and Sources: Exploring structured, unstructured, and semi-structured data sources.
- Data Lifecycle: Understanding the journey of data from collection to analysis.
Module 2: Introduction to Artificial Intelligence (1.5 hours)
- AI Basics: Defining artificial intelligence and its applications.
- Types of AI: Exploring narrow (weak) AI and general (strong) AI.AI in Everyday Life: Recognizing AI-powered technologies in our daily routines.
Module 3: Fundamentals of Machine Learning (1.5 hours)
- What is Machine Learning?: Exploring the basics of ML and its role in AI.
- Supervised vs. Unsupervised Learning: Understanding the two main categories of ML.
- Real-World Examples: Showcasing how ML is used in recommendation systems, image recognition, and more.
Module 4: Data-Driven Decision-Making (1 hour)
- Importance of Data-Driven Decisions: How data influences business strategies.
- Data Analytics: Exploring how data is analyzed to extract insights.
- Benefits and Challenges: Discussing the advantages and potential pitfalls of data-driven decisions.
Module 5: Applications and Impact (1 hour)
- AI and Industry Transformation: Examining how AI is reshaping industries like healthcare, finance, and manufacturing.
- Future Trends: Discussing emerging trends in AI and data-driven technologies.
Module 6: Q&A and Wrap-Up (30 minutes)
- Interactive Q&A: Addressing participant questions and concerns.
- Key Takeaways: Summarizing the main concepts learned throughout the training.
Training Delivery
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Engaging presentations with relatable examples.
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Interactive discussions and opportunities for participant engagement.
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Visual aids and real-world case studies to illustrate concepts.
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Q&A sessions to clarify doubts and enhance understanding.
Training Delivery
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Solid grasp of data, AI, and ML concepts for informed decision-making.
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Insights into how data-driven strategies and AI technologies are shaping industries.
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Foundation for further exploration in AI and data sciences.
Contact us to Learn More
For inquiries about our Introduction to Data, AI, and Machine Learning Training and its potential to empower your team, please contact support@ethosai.ai.
Or Contact Us: support@ethosai.ai
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Ali Hessami is currently the Director of R&D and Innovation at Vega Systems, London, UK. He has an extensive track record in systems assurance and safety, security, sustainability, knowledge assessment/management methodologies. He has a background in the design and development of advanced control systems for business and safety-critical industrial applications.
Hessami represents the UK on the European Committee for Electrotechnical Standardization (CENELEC) & International Electrotechnical Commission (IEC) – safety systems, hardware & software standards committees. He was appointed by CENELEC as convener of several Working Groups for review of EN50128 Safety-Critical Software Standard and update and restructuring of the software, hardware, and system safety standards in CENELEC.
Ali is also a member of Cyber Security Standardisation SGA16, SG24, and WG26 Groups and started and chairs the IEEE Special Interest Group in Humanitarian Technologies and the Systems Council Chapters in the UK and Ireland Section. In 2017 Ali joined the IEEE Standards Association (SA), initially as a committee member for the new landmark IEEE 7000 standard focused on “Addressing Ethical Concerns in System Design.” He was subsequently appointed as the Technical Editor and later the Chair of P7000 working group. In November 2018, he was appointed as the VC and Process Architect of the IEEE’s global Ethics Certification Programme for Autonomous & Intelligent Systems (ECPAIS).
Trish advises and trains organisations internationally on Responsible AI (AI/data ethics, policy, governance), and Corporate Digital Responsibility.
Patricia has 20 years’ experience as a lawyer in data, technology and regulatory/government affairs and is a registered Solicitor in England and Wales, and the Republic of Ireland. She has authored and edited several works on law and regulation, policy, ethics, and AI.
She is an expert advisor on the Ethics Committee to the UK’s Digital Catapult Machine Intelligence Garage working with AI startups, is a Maestro (a title only given to 3 people in the world) and expert advisor “Maestro” on the IEEE’s CertifAIEd (previously known as ECPAIS) ethical certification panel, sits on IEEE’s P7003 (algorithmic bias)/P2247.4 (adaptive instructional systems)/P7010.1 (AI and ESG/UN SDGS) standards programmes, is a ForHumanity Fellow working on Independent Audit of AI Systems, is Chair of the Society for Computers and Law, and is a non-exec director on the Board of iTechlaw and on the Board of Women Leading in AI. Until 2021, Patricia was on the RSA’s online harms advisory panel, whose work contributed to the UK’s Online Safety Bill.
Trish is also a linguist and speaks fluently English, French, and German.
In 2021, Patricia was listed on the 100 Brilliant Women in AI Ethics™ and named on Computer Weekly’s longlist as one of the Most Influential Women in UK Technology in 2021.
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