AI Literacy for Non-technical People
AI Literacy for Non-technical People
Why This Training?
In today's digital age, Data, AI, and Machine Learning are not just buzzwords; they are transformative forces redefining industries, creating new opportunities, and setting standards for innovation. Whether you're new to the field or looking to solidify your foundational understanding, this immersive 1-day training will provide you with the insights and knowledge to harness the potential of these groundbreaking fields.
Duration: 1 Day (8 hours), (online / virtual live session)
Who Should Attend?
Professionals looking to understand the implications of AI and ML in their industry.
Managers and decision-makers seeking data-driven strategies.
Entrepreneurs aspiring to leverage AI for their ventures.
Students and enthusiasts keen on building a career in AI or ML.
Managers and decision-makers seeking data-driven strategies.
Entrepreneurs aspiring to leverage AI for their ventures.
Students and enthusiasts keen on building a career in AI or ML.
Course Highlights
Dive deep into the significance of data in today's world.
Understand the distinctions and applications of AI and Machine Learning.
Explore popular machine learning algorithms and their real-world applications.
Understand the distinctions and applications of AI and Machine Learning.
Explore popular machine learning algorithms and their real-world applications.
See more
Engage in a hands-on machine learning project.
Delve into the future landscape of AI and ML, and discover upcoming trends.
Participate in a lively Q&A session to clarify doubts and foster discussions.
Delve into the future landscape of AI and ML, and discover upcoming trends.
Participate in a lively Q&A session to clarify doubts and foster discussions.
Pre-requisites
Basic understanding of computers and software.
Curiosity and willingness to learn.
No prior knowledge of AI or Machine Learning is required.
Curiosity and willingness to learn.
No prior knowledge of AI or Machine Learning is required.
Training Materials Needed by Participants
A laptop with a stable internet connection.
Note-taking materials (digital or physical).
Recommended: A free account on a platform like Google Colab for the hands-on activity (instructions to be provided prior to the training).
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Training Content
AI Literacy for Non-technical People
Objective: Provide participants with a solid foundation on data-driven decision-making processes, an introduction to the world of Artificial Intelligence, and a comprehensive understanding of machine learning basics.
Session 1: Unveiling the Power of Data
- The Age of Data: Why Data Matters.
- Types of Data: Structured, Unstructured, and Semi-Structured.
- Data Sources and Gathering: Where and how do we get our data?
- The Role of Data in Decision Making: Real-world examples.
Session 2: Demystifying Artificial Intelligence
- AI: Past, Present, and Future.
- Defining AI: What it is and isn't.
- Applications of AI: Everyday scenarios and business implications.
- The Relationship Between Data and AI.
Session 3: Introduction to Machine Learning
- What is Machine Learning? Understanding its significance.
- Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning.
- The Machine Learning Process: From data collection to predictions.
- Case Study: Successful deployment of a machine learning model.
Session 4: Diving Deeper into Algorithms
- Popular Machine Learning Algorithms and their applications.
- Overfitting, Underfitting, and Model Evaluation.
- The concept of Training and Testing Data.
Session 5: Real-world Applications and Case Studies
- Exploring real-world successes and failures in AI and ML.
- Ethical Considerations: Bias, fairness, and transparency.
- Potential impacts on industries: Healthcare, finance, entertainment, etc.
Session 6: The Future Landscape of AI and ML
- The evolving world of AI and ML: What to expect?
- Job roles and career opportunities in the field.
- Upcoming trends and technologies to watch.
Session 7: Hands-on Activity: A Simple Machine Learning Project
- Guided activity: Building a basic prediction model.
- Using a popular tool/platform for implementation.
- Interpretation of results and fine-tuning.
Session 8: Wrapping Up and Engaging Q&A
- Recap of the Day: Summarizing key learnings.
- Open Floor Q&A: Addressing queries and facilitating discussions.
- Further Resources: Directing attendees to platforms, courses, and reading material to dive deeper.
WOMEN AI ACADEMY
Women AI Academy is a gender-equality and technology driven learning & development organization
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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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