{"course":{"productid":35339,"modality":6,"active":true,"language":"fr","title":"Artificial Intelligence Foundation","productcode":"HQ7H8S","vendorcode":"HP","vendorname":"HP","fullproductcode":"HP-HQ7H8S","courseware":{"has_ekit":false,"has_printkit":true,"language":""},"url":"https:\/\/portal.flane.ch\/course\/hewlettpackard-hq7h8s","objective":"<p>In this course, students will learn to:\n<\/p>\n<ul>\n<li>Describe how artificial intelligence (AI) is part of &lsquo;Universal Design&rsquo; and &lsquo;The Fourth Industrial Revolution&rsquo;<\/li><li>Demonstrate understanding of the artificial intelligence (AI) intelligent agent description<\/li><li>Explain the benefits of artificial intelligence (AI)<\/li><li>Describe how we learn from data&mdash;functionality, software and hardware<\/li><li>Demonstrate an understanding that artificial intelligence (AI) (in particular, machine learning&mdash;ML) will drive humans and machines to work together<\/li><li>Describe a &lsquo;learning from experience&rsquo; Agile approach to projects<\/li><\/ul>","audience":"<p>The EXIN BCS Artificial Intelligence \nFoundation certification is focused on \nindividuals with an interest in (or need to \nimplement) AI in an organization&mdash; \nespecially those working in areas such as \nscience, engineering, knowledge engineering, \nfinance, education or IT services.<\/p>","contents":"<ul>\n<li>Introduction and Course Outline<\/li><li>Human and Artificial Intelligence&mdash;Part 1<\/li><li>Exercise 1<\/li><li>Human and Artificial Intelligence&mdash;Part 2<\/li><li>Ethics and Sustainability &ndash; Trustworthy AI&mdash;Part 1<\/li><li>Ethics and Sustainability &ndash; Trustworthy AI&mdash;Part 2<\/li><li>Sustainability, Universal Design, Fourth Industrial Revolution and Machine Learning<\/li><li>Exercise Two<\/li><li>Being Human, Conscious, Competent and Adaptable<\/li><li>Exercise Three<\/li><li>Applying the Benefits of AI<\/li><li>Applying the Benefits of AI<\/li><li>Building a Machine Learning Toolbox<\/li><li>Building a Machine Learning Toolbox<\/li><li>Exercise Four<\/li><li>Building a Machine Learning Toolbox &ndash; Two Case Studies<\/li><li>Building a Machine Learning Toolbox<\/li><li>Building a Machine Learning Toolbox<\/li><li>Building a Machine Learning Toolbox<\/li><li>A Simple Neural Network Schematic<\/li><li>Exercise Five<\/li><li>Machine Learning and Consciousness<\/li><li>The Future of Artificial Intelligence<\/li><li>Exercise Six<\/li><li>Learning from Experience<\/li><li>Conclusion<\/li><li>Exam Practice and Preparation<\/li><li>Examination<\/li><\/ul>","outline":"<h5>Introduction and Course Outline <\/h5><ul>\n<li>Course overview and structure<\/li><li>Exam information<\/li><li>Daily schedule<\/li><\/ul><h5>Human and Artificial Intelligence&mdash;Part 1 <\/h5><ul>\n<li>General definition of AI<\/li><li>Ethics<\/li><li>Sustainability<\/li><li>AI as part of Universal Design and The Fourth Industrial Revolution<\/li><li>Challenges and risks<\/li><\/ul><h5>Exercise 1 <\/h5><ul>\n<li>Opportunities for AI<\/li><\/ul><h5>Human and Artificial Intelligence&mdash;Part 2 <\/h5><ul>\n<li>Learning from experience<\/li><li>Applying the benefits of AI<\/li><li>Opportunities<\/li><\/ul><h5>Ethics and Sustainability &ndash; Trustworthy AI&mdash;Part 1<\/h5><ul>\n<li>Roles and responsibilities of humans and machines<\/li><\/ul><h5>Ethics and Sustainability &ndash; Trustworthy AI&mdash;Part 2<\/h5><ul>\n<li>Trustworthy AI<\/li><\/ul><h5>Sustainability, Universal Design, Fourth Industrial Revolution and Machine Learning<\/h5><ul>\n<li>Learning from data, functionality, software and hardware<\/li><\/ul><h5> Exercise Two <\/h5><ul>\n<li>Ethics and sustainability<\/li><\/ul><ul>\n<li>Artificial Intelligent Agents and Robotics<\/li><\/ul><ul>\n<li>AI intelligent agent description<\/li><li>What a robot is<\/li><li>What an intelligent robot is<\/li><\/ul><h5> Being Human, Conscious, Competent and Adaptable<\/h5><ul>\n<li>AI project teams<\/li><li>Modelling humans<\/li><\/ul><h5>Exercise Three<\/h5><ul>\n<li>Human plus machine mindmap<\/li><\/ul><h5>What is a Robot?<\/h5><ul>\n<li>Definition of a robot<\/li><li>Robot paradigm<\/li><\/ul><h5>Applying the Benefits of AI <\/h5><ul>\n<li>Benefits, challenges and risks<\/li><\/ul><h5>Applying the Benefits of AI <\/h5><ul>\n<li>Opportunities and funding<\/li><\/ul><h5>Building a Machine Learning Toolbox <\/h5><ul>\n<li>How do we learn from data?<\/li><\/ul><h5>Building a Machine Learning Toolbox <\/h5><ul>\n<li>Types of machine learning<\/li><\/ul><h5>Exercise Four <\/h5><ul>\n<li>Define a simple ML problem<\/li><\/ul>\n<h5>Building a Machine Learning Toolbox &ndash; Two Case Studies<\/h5><h5>Building a Machine Learning Toolbox <\/h5><ul>\n<li>Introduction to probability and statistics<\/li><\/ul><h5>Building a Machine Learning Toolbox<\/h5>\n<ul>\n<li>Introduction to linear algebra and vector calculus<\/li><\/ul><h5>Building a Machine Learning Toolbox<\/h5><ul>\n<li>Visualising data<\/li><\/ul><h5>A Simple Neural Network Schematic <\/h5><ul>\n<li>Introduction to neural networks<\/li><\/ul><h5>Exercise Five <\/h5><ul>\n<li>Maturity and funding of an AI system<\/li><\/ul>\n<h5>Open Source ML and Robotic Systems <\/h5><ul>\n<li>Open source software for AI and robotics<\/li><\/ul><h5>Machine Learning and Consciousness <\/h5><ul>\n<li>Introduction to machine learning and consciousness<\/li><\/ul>\n<h5>The Future of Artificial Intelligence <\/h5><ul>\n<li>The human + machine<\/li><li>What will drive humans and machines to work together<\/li><\/ul>\n<h5>Exercise Six <\/h5><ul>\n<li>Explore the future opportunities for AI and human systems<\/li><\/ul><h5>Learning from Experience<\/h5>\n<ul>\n<li>Agile projects<\/li><\/ul>\n<h5>Conclusion<\/h5><h5>Exam Practice and Preparation<\/h5><h5>Examination<\/h5>","summary":"<p>rtificial Intelligence (AI) is a methodology for using a non\u0002human system to learn from experience and imitate human \nintelligent behavior. \nThis training covers the potential benefits and challenges of \nethical and sustainable robust Artificial Intelligence (AI); the \nbasic process of Machine Learning (ML) &ndash; Building a Machine \nLearning (ML) Toolkit; the challenges and risks associated \nwith an AI project, and the future of AI and Humans in work. \nThis course prepares for the EXIN BCS Artificial Intelligence \nFoundation certification\nWhat is a Robot?<\/p>","objective_plain":"In this course, students will learn to:\n\n\n\n- Describe how artificial intelligence (AI) is part of \u2018Universal Design\u2019 and \u2018The Fourth Industrial Revolution\u2019\n- Demonstrate understanding of the artificial intelligence (AI) intelligent agent description\n- Explain the benefits of artificial intelligence (AI)\n- Describe how we learn from data\u2014functionality, software and hardware\n- Demonstrate an understanding that artificial intelligence (AI) (in particular, machine learning\u2014ML) will drive humans and machines to work together\n- Describe a \u2018learning from experience\u2019 Agile approach to projects","audience_plain":"The EXIN BCS Artificial Intelligence \nFoundation certification is focused on \nindividuals with an interest in (or need to \nimplement) AI in an organization\u2014 \nespecially those working in areas such as \nscience, engineering, knowledge engineering, \nfinance, education or IT services.","contents_plain":"- Introduction and Course Outline\n- Human and Artificial Intelligence\u2014Part 1\n- Exercise 1\n- Human and Artificial Intelligence\u2014Part 2\n- Ethics and Sustainability \u2013 Trustworthy AI\u2014Part 1\n- Ethics and Sustainability \u2013 Trustworthy AI\u2014Part 2\n- Sustainability, Universal Design, Fourth Industrial Revolution and Machine Learning\n- Exercise Two\n- Being Human, Conscious, Competent and Adaptable\n- Exercise Three\n- Applying the Benefits of AI\n- Applying the Benefits of AI\n- Building a Machine Learning Toolbox\n- Building a Machine Learning Toolbox\n- Exercise Four\n- Building a Machine Learning Toolbox \u2013 Two Case Studies\n- Building a Machine Learning Toolbox\n- Building a Machine Learning Toolbox\n- Building a Machine Learning Toolbox\n- A Simple Neural Network Schematic\n- Exercise Five\n- Machine Learning and Consciousness\n- The Future of Artificial Intelligence\n- Exercise Six\n- Learning from Experience\n- Conclusion\n- Exam Practice and Preparation\n- Examination","outline_plain":"Introduction and Course Outline \n\n\n- Course overview and structure\n- Exam information\n- Daily schedule\nHuman and Artificial Intelligence\u2014Part 1 \n\n\n- General definition of AI\n- Ethics\n- Sustainability\n- AI as part of Universal Design and The Fourth Industrial Revolution\n- Challenges and risks\nExercise 1 \n\n\n- Opportunities for AI\nHuman and Artificial Intelligence\u2014Part 2 \n\n\n- Learning from experience\n- Applying the benefits of AI\n- Opportunities\nEthics and Sustainability \u2013 Trustworthy AI\u2014Part 1\n\n\n- Roles and responsibilities of humans and machines\nEthics and Sustainability \u2013 Trustworthy AI\u2014Part 2\n\n\n- Trustworthy AI\nSustainability, Universal Design, Fourth Industrial Revolution and Machine Learning\n\n\n- Learning from data, functionality, software and hardware\n Exercise Two \n\n\n- Ethics and sustainability\n\n- Artificial Intelligent Agents and Robotics\n\n- AI intelligent agent description\n- What a robot is\n- What an intelligent robot is\n Being Human, Conscious, Competent and Adaptable\n\n\n- AI project teams\n- Modelling humans\nExercise Three\n\n\n- Human plus machine mindmap\nWhat is a Robot?\n\n\n- Definition of a robot\n- Robot paradigm\nApplying the Benefits of AI \n\n\n- Benefits, challenges and risks\nApplying the Benefits of AI \n\n\n- Opportunities and funding\nBuilding a Machine Learning Toolbox \n\n\n- How do we learn from data?\nBuilding a Machine Learning Toolbox \n\n\n- Types of machine learning\nExercise Four \n\n\n- Define a simple ML problem\n\nBuilding a Machine Learning Toolbox \u2013 Two Case Studies\n\nBuilding a Machine Learning Toolbox \n\n\n- Introduction to probability and statistics\nBuilding a Machine Learning Toolbox\n\n\n\n- Introduction to linear algebra and vector calculus\nBuilding a Machine Learning Toolbox\n\n\n- Visualising data\nA Simple Neural Network Schematic \n\n\n- Introduction to neural networks\nExercise Five \n\n\n- Maturity and funding of an AI system\n\nOpen Source ML and Robotic Systems \n\n\n- Open source software for AI and robotics\nMachine Learning and Consciousness \n\n\n- Introduction to machine learning and consciousness\n\nThe Future of Artificial Intelligence \n\n\n- The human + machine\n- What will drive humans and machines to work together\n\nExercise Six \n\n\n- Explore the future opportunities for AI and human systems\nLearning from Experience\n\n\n\n- Agile projects\n\nConclusion\n\nExam Practice and Preparation\n\nExamination","summary_plain":"rtificial Intelligence (AI) is a methodology for using a non\u0002human system to learn from experience and imitate human \nintelligent behavior. \nThis training covers the potential benefits and challenges of \nethical and sustainable robust Artificial Intelligence (AI); the \nbasic process of Machine Learning (ML) \u2013 Building a Machine \nLearning (ML) Toolkit; the challenges and risks associated \nwith an AI project, and the future of AI and Humans in work. \nThis course prepares for the EXIN BCS Artificial Intelligence \nFoundation certification\nWhat is a Robot?","version":"1.0","duration":{"unit":"d","value":3,"formatted":"3 jours"},"pricelist":{"List Price":{"DE":{"country":"DE","currency":"EUR","taxrate":19,"price":2250},"AT":{"country":"AT","currency":"EUR","taxrate":20,"price":2250},"SI":{"country":"SI","currency":"EUR","taxrate":20,"price":2250}}},"lastchanged":"2025-01-10T01:17:43+01:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course-schedule\/35339","source_lang":"fr","source":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course\/hewlettpackard-hq7h8s"}}