Best Ethical AI Courses to Learn in January 2025
Looking to enhance your skills? We’ve curated a list of the top-rated ethical AI courses available this month. These courses are highly rated by students and offer comprehensive learning experiences.
10. 2025 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI
Instructor: Julio Colomer
From zero to professional level: learn the keys to Generative AI, LLM Apps, AI Agents, and Cursor AI.
Course Highlights:
- Rating: 4.53 ⭐ (1646 reviews)
- Students Enrolled: 16779
- Course Length: 270513 hours
- Number of Lectures: 663
- Number of Quizzes: 0
2025 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI, has an average rating of 4.53, with 663 lectures, based on 1646 reviews, and has 16779 subscribers.
You will learn about Keys to AI, Generative AI, LLM Apps, and new AI Coding Assistants like Cursor AI. LLM Apps with LangChain, CrewAI, LangGraph, LangServe and LangSmith. How to build apps without coding using Cursor AI and AI Coding Assistants. How to build the new Multimodal and Multi-Agent LLM Applications. Opportunities and threats of AI for businesses, startups, and jobs. RAG Applications in Depth: Full Stack RAG Apps and Advanced Techniques. How to manage LLMOps: Observability, Evaluation, Testing, Etc. Professional opportunities opened by Artificial Intelligence. Steps to become an Artificial Intelligence Engineer. How to introduce Artificial Intelligence into your business. Keys to LLM Applications, the highest potential applications of Generative AI. Architecture of professional LLM Applications. The RAG Technique (Retrieval Augmented Generation). Artificial Intelligence Agents. Basic and advanced LangChain, LangChain LCEL, and LangChain v010. LangSmith, LangServe, LangChain Templates. LCEL (LangChain Expression Language) in depth. Basic and advanced LlamaIndex. LlamaIndex Templates. ChatGPT, OpenAI, OpenAI functions, and the OpenAI API. Large Language Models (LLM): ChatGPT, Llama2, Mistral, Falcon, etc. Vector databases: Postgres, Pinecone, Chroma, FAISS, DeepLake, etc. Full-Stack Applications: Nextjs and FastAPI. Professional deployment: Vercel and Render. Provisional deployment: Streamlit. Cloud hosting: AWS S3. How to apply the principles of Responsible AI. Daily tools of the AI Engineer: Jupyter Notebooks, Python, Terminal, Github, Codespaces, etc. This course is ideal for individuals who are Students and professionals with and without previous experience. or Students without prior knowledge interested in taking advantage of the professional opportunities opened by the field of Artificial Intelligence. or Executives interested in introducing Artificial Intelligence into their company. or Machine Learning, Deep Learning, and Data Science professionals interested in expanding their professional opportunities in the area of Generative AI and LLM Applications. or Software application developers interested in expanding their professional opportunities by learning to develop Generative Artificial Intelligence and LLM Applications. It is particularly useful for Students and professionals with and without previous experience. or Students without prior knowledge interested in taking advantage of the professional opportunities opened by the field of Artificial Intelligence. or Executives interested in introducing Artificial Intelligence into their company. or Machine Learning, Deep Learning, and Data Science professionals interested in expanding their professional opportunities in the area of Generative AI and LLM Applications. or Software application developers interested in expanding their professional opportunities by learning to develop Generative Artificial Intelligence and LLM Applications.
Learn More About 2025 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI
What You Will Learn
- Keys to AI, Generative AI, LLM Apps, and new AI Coding Assistants like Cursor AI.
- LLM Apps with LangChain, CrewAI, LangGraph, LangServe and LangSmith.
- How to build apps without coding using Cursor AI and AI Coding Assistants.
- How to build the new Multimodal and Multi-Agent LLM Applications.
- Opportunities and threats of AI for businesses, startups, and jobs.
- RAG Applications in Depth: Full Stack RAG Apps and Advanced Techniques.
- How to manage LLMOps: Observability, Evaluation, Testing, Etc.
- Professional opportunities opened by Artificial Intelligence.
- Steps to become an Artificial Intelligence Engineer.
- How to introduce Artificial Intelligence into your business.
- Keys to LLM Applications, the highest potential applications of Generative AI.
- Architecture of professional LLM Applications.
- The RAG Technique (Retrieval Augmented Generation).
- Artificial Intelligence Agents.
- Basic and advanced LangChain, LangChain LCEL, and LangChain v010. LangSmith, LangServe, LangChain Templates.
- LCEL (LangChain Expression Language) in depth.
- Basic and advanced LlamaIndex. LlamaIndex Templates.
- ChatGPT, OpenAI, OpenAI functions, and the OpenAI API.
- Large Language Models (LLM): ChatGPT, Llama2, Mistral, Falcon, etc.
- Vector databases: Postgres, Pinecone, Chroma, FAISS, DeepLake, etc.
- Full-Stack Applications: Nextjs and FastAPI.
- Professional deployment: Vercel and Render.
- Provisional deployment: Streamlit.
- Cloud hosting: AWS S3.
- How to apply the principles of Responsible AI.
- Daily tools of the AI Engineer: Jupyter Notebooks, Python, Terminal, Github, Codespaces, etc.
9. GenAI and Cybersecurity – Frameworks and Best Practices 2024
Instructor: Sivaram A
Build and Secure Enterprise GenAI Adoption, Tools, Frameworks and Production Case Studies from Leaders
Course Highlights:
- Rating: 4.83 ⭐ (12 reviews)
- Students Enrolled: 84
- Course Length: 23624 hours
- Number of Lectures: 165
- Number of Quizzes: 17
GenAI and Cybersecurity – Frameworks and Best Practices 2024, has an average rating of 4.83, with 165 lectures, 17 quizzes, based on 12 reviews, and has 84 subscribers.
You will learn about Master the foundational principles and best practices for integrating Generative AI in cybersecurity. Become aware about AI, ML, and deep learning, focusing on their applications in various industries, including a case study on Tesla Autopilot. Study the intersection of AI/ML and cybersecurity, understanding ethical considerations and potential risks with examples from real-world scenarios. Explore the latest trends as per industry reports like those from Gartner. Delve into typical cloud-based and AI-specific cybersecurity architectures, learning how they differ and why they're essential. Develop strategies for managing AI data privacy, including data quality, governance, and lifecycle management. Learn about AI risk management frameworks like NIST AI RMF, and explore case studies on navigating AI risks. Understand key AI controls and policies, including the CIA Triad, OWASP AI vulnerabilities, and AI governance frameworks. Gain knowledge about auditing AI systems, understanding components of compliance, and readiness comparisons. Explore various AI regulatory frameworks, including the EU AI Act, GDPR, and ethical AI frameworks by OECD. Understand the security implications of Generative AI, exploring defenses, future challenges, and opportunities. Learn about innovative GenAI solutions and opportunities, including custom LLM implementations and industry-specific applications. Understand how AI can be used to enhance governance practices and develop frameworks for low-risk AI adoption. Study key controversies and ethical issues in AI, as outlined by UNESCO and other bodies, to inform responsible AI practices. This course is ideal for individuals who are Product Managers: Ideal for those adopting LLM-based solutions, this course will help you enhance product development and ensure secure implementation. or Data Scientists: Perfect for professionals aiming to integrate GenAI with data-driven projects, manage biases, and mitigate security risks effectively. or Cybersecurity Teams: Essential for cybersecurity and CISO teams involved in AI/ML and GenAI adoption, focusing on securing AI initiatives and understanding emerging threats. or Business Leaders and Executives: Beneficial for business leaders and executives targeting GenAI-based use case adoption, driving innovation while maintaining compliance and security. or Innovative Problem Solvers: Suited for creative thinkers who enjoy tackling complex challenges with cutting-edge technology and AI-driven solutions. or IT Professionals: Crucial for IT experts responsible for managing and securing AI infrastructure, ensuring robust cybersecurity measures are in place. or AI Enthusiasts and Tech Innovators: Great for individuals passionate about AI, looking to stay updated with the latest trends and advancements in Generative AI and cybersecurity. or Compliance Officers and Legal Experts: Valuable for professionals overseeing compliance and regulatory aspects, providing insights into AI frameworks, policies, and ethical considerations. It is particularly useful for Product Managers: Ideal for those adopting LLM-based solutions, this course will help you enhance product development and ensure secure implementation. or Data Scientists: Perfect for professionals aiming to integrate GenAI with data-driven projects, manage biases, and mitigate security risks effectively. or Cybersecurity Teams: Essential for cybersecurity and CISO teams involved in AI/ML and GenAI adoption, focusing on securing AI initiatives and understanding emerging threats. or Business Leaders and Executives: Beneficial for business leaders and executives targeting GenAI-based use case adoption, driving innovation while maintaining compliance and security. or Innovative Problem Solvers: Suited for creative thinkers who enjoy tackling complex challenges with cutting-edge technology and AI-driven solutions. or IT Professionals: Crucial for IT experts responsible for managing and securing AI infrastructure, ensuring robust cybersecurity measures are in place. or AI Enthusiasts and Tech Innovators: Great for individuals passionate about AI, looking to stay updated with the latest trends and advancements in Generative AI and cybersecurity. or Compliance Officers and Legal Experts: Valuable for professionals overseeing compliance and regulatory aspects, providing insights into AI frameworks, policies, and ethical considerations.
Learn More About GenAI and Cybersecurity – Frameworks and Best Practices 2024
What You Will Learn
- Master the foundational principles and best practices for integrating Generative AI in cybersecurity.
- Become aware about AI, ML, and deep learning, focusing on their applications in various industries, including a case study on Tesla Autopilot.
- Study the intersection of AI/ML and cybersecurity, understanding ethical considerations and potential risks with examples from real-world scenarios.
- Explore the latest trends as per industry reports like those from Gartner.
- Delve into typical cloud-based and AI-specific cybersecurity architectures, learning how they differ and why they're essential.
- Develop strategies for managing AI data privacy, including data quality, governance, and lifecycle management.
- Learn about AI risk management frameworks like NIST AI RMF, and explore case studies on navigating AI risks.
- Understand key AI controls and policies, including the CIA Triad, OWASP AI vulnerabilities, and AI governance frameworks.
- Gain knowledge about auditing AI systems, understanding components of compliance, and readiness comparisons.
- Explore various AI regulatory frameworks, including the EU AI Act, GDPR, and ethical AI frameworks by OECD.
- Understand the security implications of Generative AI, exploring defenses, future challenges, and opportunities.
- Learn about innovative GenAI solutions and opportunities, including custom LLM implementations and industry-specific applications.
- Understand how AI can be used to enhance governance practices and develop frameworks for low-risk AI adoption.
- Study key controversies and ethical issues in AI, as outlined by UNESCO and other bodies, to inform responsible AI practices.
8. AI Literacy Basics: Applying Generative AI in the Workplace
Instructor: Nicolle Merrill
Practical AI for beginners. Learn generative AI tools for your job, no programming or tech background required.
Course Highlights:
- Rating: 4.67 ⭐ (59 reviews)
- Students Enrolled: 272
- Course Length: 15403 hours
- Number of Lectures: 56
- Number of Quizzes: 0
AI Literacy Basics: Applying Generative AI in the Workplace, has an average rating of 4.67, with 56 lectures, based on 59 reviews, and has 272 subscribers.
You will learn about Demonstrate the ability to use at least three generative AI tools relevant to your job function. Apply prompt engineering techniques to effectively communicate with AI tools for improved results. Develop a strategy for integrating generative AI tools into your daily work routine to enhance productivity. Identify at least five practical applications of generative AI in various business functions. Evaluate the potential benefits and limitations of implementing generative AI in your role. Formulate effective questions and prompts to maximize the utility of generative AI in problem-solving scenarios. Adapt existing workflows to incorporate generative AI tools for improved efficiency. Articulate the potential impact of generative AI on your industry and career trajectory. Communicate the value and limitations of generative AI to both technical and non-technical stakeholders. Create a personal action plan for continuous learning and skill development in the field of AI. This course is ideal for individuals who are This course on AI Literacy and using generative AI tools in the workplace is designed specifically for business professionals and working professionals who do not have a programming or technical background. It caters to individuals across various industries, job roles, and departments who want to develop a practical understanding of generative AI and how to effectively leverage these tools to enhance their productivity and job performance, without needing to learn how to code or get into the technical weeds. or Whether you're in marketing, sales, operations, HR, finance, project management or any other business function, this course will empower you to become AI-literate and harness the potential of generative AI in your specific workplace context. No prior programming experience is required. The curriculum is tailored for non-technical professionals, focusing on building conceptual knowledge about generative AI, applying critical thinking to its uses and implications, and gaining hands-on experience with user-friendly generative AI applications relevant to typical business workflows. It is particularly useful for This course on AI Literacy and using generative AI tools in the workplace is designed specifically for business professionals and working professionals who do not have a programming or technical background. It caters to individuals across various industries, job roles, and departments who want to develop a practical understanding of generative AI and how to effectively leverage these tools to enhance their productivity and job performance, without needing to learn how to code or get into the technical weeds. or Whether you're in marketing, sales, operations, HR, finance, project management or any other business function, this course will empower you to become AI-literate and harness the potential of generative AI in your specific workplace context. No prior programming experience is required. The curriculum is tailored for non-technical professionals, focusing on building conceptual knowledge about generative AI, applying critical thinking to its uses and implications, and gaining hands-on experience with user-friendly generative AI applications relevant to typical business workflows.
Learn More About AI Literacy Basics: Applying Generative AI in the Workplace
What You Will Learn
- Demonstrate the ability to use at least three generative AI tools relevant to your job function.
- Apply prompt engineering techniques to effectively communicate with AI tools for improved results.
- Develop a strategy for integrating generative AI tools into your daily work routine to enhance productivity.
- Identify at least five practical applications of generative AI in various business functions.
- Evaluate the potential benefits and limitations of implementing generative AI in your role.
- Formulate effective questions and prompts to maximize the utility of generative AI in problem-solving scenarios.
- Adapt existing workflows to incorporate generative AI tools for improved efficiency.
- Articulate the potential impact of generative AI on your industry and career trajectory.
- Communicate the value and limitations of generative AI to both technical and non-technical stakeholders.
- Create a personal action plan for continuous learning and skill development in the field of AI.
7. Change Management for Generative AI
Instructor: Peter Alkema
Master Change Management with Generative AI: Leadership, Resistance Handling, Ethical AI Use, and Innovation Strategy
Course Highlights:
- Rating: 4.63 ⭐ (4 reviews)
- Students Enrolled: 98
- Course Length: 19766 hours
- Number of Lectures: 108
- Number of Quizzes: 22
Change Management for Generative AI, has an average rating of 4.63, with 108 lectures, 22 quizzes, based on 4 reviews, and has 98 subscribers.
You will learn about Explain the fundamentals of change management in the context of generative AI technologies. Describe how generative AI is transforming traditional change management processes. Analyze the challenges and opportunities presented by AI-driven change in organizational settings. Evaluate real-life examples of change management in generative AI to identify best practices. Lead AI transformation projects effectively by applying proven leadership strategies in change management. Assign roles and responsibilities to team members in AI change initiatives to ensure successful outcomes. Develop a comprehensive change management strategy for generative AI adoption. Diagnose resistance to generative AI adoption and develop strategies to address it. Utilize communication techniques to reduce resistance and enhance acceptance of generative AI projects. Cultivate a culture of innovation within an organization to support generative AI initiatives. Foster collaboration and creativity in teams working on generative AI projects. Communicate the benefits and impacts of generative AI adoption to various stakeholders effectively. Align organizational strategies with generative AI implementation to achieve business goals. Assess organizational readiness for generative AI projects using a structured framework. Promote diversity and inclusion within AI teams to enhance project outcomes. Apply ethical guidelines in decision-making processes for generative AI projects. Measure the success of generative AI change initiatives using key performance indicators. Build resilience in teams to adapt to challenges faced during generative AI transformation. Implement agile project management methodologies in generative AI projects to enhance flexibility and responsiveness. Innovate with generative AI technologies to maintain competitive advantage and drive business success. This course is ideal for individuals who are Organizational leaders seeking to introduce or expand the use of Generative AI in their companies. or Change management professionals looking to specialize in AI-driven transformation initiatives. or IT and AI project managers aiming to incorporate effective change management strategies in their projects. or HR and talent development professionals tasked with facilitating a culture that embraces AI innovations. or Diversity and inclusion officers focusing on ensuring AI initiatives are inclusive and equitable. or Regulatory and compliance professionals within organizations adopting Generative AI technologies. It is particularly useful for Organizational leaders seeking to introduce or expand the use of Generative AI in their companies. or Change management professionals looking to specialize in AI-driven transformation initiatives. or IT and AI project managers aiming to incorporate effective change management strategies in their projects. or HR and talent development professionals tasked with facilitating a culture that embraces AI innovations. or Diversity and inclusion officers focusing on ensuring AI initiatives are inclusive and equitable. or Regulatory and compliance professionals within organizations adopting Generative AI technologies.
Learn More About Change Management for Generative AI
What You Will Learn
- Explain the fundamentals of change management in the context of generative AI technologies.
- Describe how generative AI is transforming traditional change management processes.
- Analyze the challenges and opportunities presented by AI-driven change in organizational settings.
- Evaluate real-life examples of change management in generative AI to identify best practices.
- Lead AI transformation projects effectively by applying proven leadership strategies in change management.
- Assign roles and responsibilities to team members in AI change initiatives to ensure successful outcomes.
- Develop a comprehensive change management strategy for generative AI adoption.
- Diagnose resistance to generative AI adoption and develop strategies to address it.
- Utilize communication techniques to reduce resistance and enhance acceptance of generative AI projects.
- Cultivate a culture of innovation within an organization to support generative AI initiatives.
- Foster collaboration and creativity in teams working on generative AI projects.
- Communicate the benefits and impacts of generative AI adoption to various stakeholders effectively.
- Align organizational strategies with generative AI implementation to achieve business goals.
- Assess organizational readiness for generative AI projects using a structured framework.
- Promote diversity and inclusion within AI teams to enhance project outcomes.
- Apply ethical guidelines in decision-making processes for generative AI projects.
- Measure the success of generative AI change initiatives using key performance indicators.
- Build resilience in teams to adapt to challenges faced during generative AI transformation.
- Implement agile project management methodologies in generative AI projects to enhance flexibility and responsiveness.
- Innovate with generative AI technologies to maintain competitive advantage and drive business success.
6. AI Fundamentals for Business Professionals
Instructor: Peter Alkema
Mastering AI Leadership: Strategies, Ethics & Innovation for 2025 and Beyond
Course Highlights:
- Rating: 4.74 ⭐ (21 reviews)
- Students Enrolled: 80
- Course Length: 19609 hours
- Number of Lectures: 108
- Number of Quizzes: 22
AI Fundamentals for Business Professionals, has an average rating of 4.74, with 108 lectures, 22 quizzes, based on 21 reviews, and has 80 subscribers.
You will learn about Explain the fundamentals of AI to understand its impact on leadership and management strategies. Evaluate the ethical considerations necessary for integrating AI into leadership practices. Develop AI adoption strategies to enhance organizational leadership and management. Analyze real-world examples of leaders who have successfully embraced AI in their strategies. Apply AI tools to assist in strategic decision-making processes for business growth. Formulate strategic plans incorporating AI insights to achieve competitive advantage. Enhance emotional intelligence skills by leveraging AI technologies for better leadership outcomes. Demonstrate empathy in leadership roles by integrating AI to understand diverse team member needs. Foster a culture of innovation within teams by utilizing AI tools and methodologies. Create a vision for the future of an organization or team using AI-driven data analytics. Implement transformational leadership strategies supported by AI to drive organizational change. Promote diversity and inclusion within teams by using AI to remove bias and enhance engagement. Adapt leadership styles to changing environments with the aid of AI insights for improved decision-making. Use AI-enhanced collaboration techniques to improve teamwork and collective problem-solving. Customize personal leadership development plans using AI tools for skill assessment and growth. Navigate ethical dilemmas in leadership by applying AI ethics frameworks and principles. Build resilience in leadership roles by utilizing AI tools for managing high-pressure situations effectively. Lead virtual teams efficiently by applying AI for enhanced communication and collaboration. Develop authentic leadership qualities by utilizing AI for personal branding and authenticity challenges. Employ AI technologies for agile leadership practices to lead complex projects and environments effectively. This course is ideal for individuals who are Corporate executives looking to integrate AI into their leadership practices. or HR managers seeking innovative strategies for talent management with AI. or Team leaders who aim to improve decision-making and collaboration through AI tools. or Emerging leaders in tech companies focusing on building a culture of innovation. or Organizational development consultants specializing in transformational leadership with AI. or Diversity and inclusion officers aiming to leverage AI for more inclusive leadership practices. It is particularly useful for Corporate executives looking to integrate AI into their leadership practices. or HR managers seeking innovative strategies for talent management with AI. or Team leaders who aim to improve decision-making and collaboration through AI tools. or Emerging leaders in tech companies focusing on building a culture of innovation. or Organizational development consultants specializing in transformational leadership with AI. or Diversity and inclusion officers aiming to leverage AI for more inclusive leadership practices.
Learn More About AI Fundamentals for Business Professionals
What You Will Learn
- Explain the fundamentals of AI to understand its impact on leadership and management strategies.
- Evaluate the ethical considerations necessary for integrating AI into leadership practices.
- Develop AI adoption strategies to enhance organizational leadership and management.
- Analyze real-world examples of leaders who have successfully embraced AI in their strategies.
- Apply AI tools to assist in strategic decision-making processes for business growth.
- Formulate strategic plans incorporating AI insights to achieve competitive advantage.
- Enhance emotional intelligence skills by leveraging AI technologies for better leadership outcomes.
- Demonstrate empathy in leadership roles by integrating AI to understand diverse team member needs.
- Foster a culture of innovation within teams by utilizing AI tools and methodologies.
- Create a vision for the future of an organization or team using AI-driven data analytics.
- Implement transformational leadership strategies supported by AI to drive organizational change.
- Promote diversity and inclusion within teams by using AI to remove bias and enhance engagement.
- Adapt leadership styles to changing environments with the aid of AI insights for improved decision-making.
- Use AI-enhanced collaboration techniques to improve teamwork and collective problem-solving.
- Customize personal leadership development plans using AI tools for skill assessment and growth.
- Navigate ethical dilemmas in leadership by applying AI ethics frameworks and principles.
- Build resilience in leadership roles by utilizing AI tools for managing high-pressure situations effectively.
- Lead virtual teams efficiently by applying AI for enhanced communication and collaboration.
- Develop authentic leadership qualities by utilizing AI for personal branding and authenticity challenges.
- Employ AI technologies for agile leadership practices to lead complex projects and environments effectively.
5. Certified AI Compliance and Ethics Auditor (CACEA)
Instructor: YouAccel Training
Ensuring Ethical and Compliant AI: A Comprehensive Guide for Auditors
Course Highlights:
- Rating: 4.67 ⭐ (9 reviews)
- Students Enrolled: 1770
- Course Length: 65011 hours
- Number of Lectures: 182
- Number of Quizzes: 0
Certified AI Compliance and Ethics Auditor (CACEA), has an average rating of 4.67, with 182 lectures, based on 9 reviews, and has 1770 subscribers.
You will learn about Understand the vital role of an AI auditor in ensuring ethical practices. Learn core principles and objectives guiding AI audits. Explore fundamental AI and machine learning concepts. Study key differences between traditional and AI-driven systems. Identify and manage common risks in AI deployment. Grasp ethical principles such as fairness and non-discrimination. Gain insight into transparency and explainability requirements. Develop strategies for integrating AI governance with strategy. Familiarize with global and regional AI regulations. Understand the implications of non-compliance in AI. Master risk management frameworks for auditing AI systems. Plan and conduct comprehensive AI audits effectively. Document and report audit findings with clarity. Ensure data privacy and compliance with regulations. Evaluate AI transparency and explainability techniques. Identify and mitigate bias to achieve fair AI outcomes. This course is ideal for individuals who are Professionals aiming to understand AI ethics and compliance auditing. or Compliance officers seeking AI-specific regulatory knowledge. or Auditors transitioning to roles involving AI oversight. or Managers needing insights into AI governance structures. or Risk management experts focused on AI system evaluations. or Tech leaders integrating ethical practices in AI development. or Legal advisors specializing in AI regulations and compliance. It is particularly useful for Professionals aiming to understand AI ethics and compliance auditing. or Compliance officers seeking AI-specific regulatory knowledge. or Auditors transitioning to roles involving AI oversight. or Managers needing insights into AI governance structures. or Risk management experts focused on AI system evaluations. or Tech leaders integrating ethical practices in AI development. or Legal advisors specializing in AI regulations and compliance.
Learn More About Certified AI Compliance and Ethics Auditor (CACEA)
What You Will Learn
- Understand the vital role of an AI auditor in ensuring ethical practices.
- Learn core principles and objectives guiding AI audits.
- Explore fundamental AI and machine learning concepts.
- Study key differences between traditional and AI-driven systems.
- Identify and manage common risks in AI deployment.
- Grasp ethical principles such as fairness and non-discrimination.
- Gain insight into transparency and explainability requirements.
- Develop strategies for integrating AI governance with strategy.
- Familiarize with global and regional AI regulations.
- Understand the implications of non-compliance in AI.
- Master risk management frameworks for auditing AI systems.
- Plan and conduct comprehensive AI audits effectively.
- Document and report audit findings with clarity.
- Ensure data privacy and compliance with regulations.
- Evaluate AI transparency and explainability techniques.
- Identify and mitigate bias to achieve fair AI outcomes.
4. Artificial Intelligence Mastery: Complete AI Bootcamp 2025
Instructor: Vivian Aranha
Everything you need to know about AI Engineering – Hands-on from Algorithms, Python Programming to Real-World Projects
Course Highlights:
- Rating: 4.67 ⭐ (34 reviews)
- Students Enrolled: 5399
- Course Length: 195350 hours
- Number of Lectures: 284
- Number of Quizzes: 1
Artificial Intelligence Mastery: Complete AI Bootcamp 2025, has an average rating of 4.67, with 284 lectures, 1 quizzes, based on 34 reviews, and has 5399 subscribers.
You will learn about Master Python for AI: Write efficient Python code, essential for AI and ML programming tasks. Data Preprocessing Skills: Prepare, clean, and transform data to enhance model performance. Statistical Knowledge: Apply core statistics to understand data patterns and inform decisions. Build Machine Learning Models: Develop and fine-tune ML models for classification, regression, and clustering. Deep Learning Proficiency: Design and train neural networks, including CNNs and RNNs, for image and sequence tasks. Utilize Transfer Learning: Adapt pre-trained models to new tasks, saving time and resources. Deploy ML Models with APIs: Create scalable APIs to serve ML models in real-world applications. Containerize with Docker: Package models for portable deployment across environments. Monitor and Maintain Models: Track model performance, detect drift, and implement retraining pipelines. Complete ML Lifecycle: Master end-to-end AI project skills, from data to deployment and ongoing maintenance. This course is ideal for individuals who are Aspiring AI Engineers: Those looking to build a career in AI and gain hands-on, production-ready skills. or Data Scientists and Analysts: Professionals who want to expand their expertise to include machine learning, deep learning, and model deployment. or Software Engineers: Developers interested in applying programming skills to AI and machine learning projects. or Career Changers: Individuals from non-technical backgrounds with foundational Python knowledge, eager to transition into AI. or Graduate Students: Students in data science, computer science, or related fields wanting a practical, job-ready experience in AI engineering. or Tech Entrepreneurs: Founders and CTOs interested in understanding AI for building AI-driven products or managing AI teams. It is particularly useful for Aspiring AI Engineers: Those looking to build a career in AI and gain hands-on, production-ready skills. or Data Scientists and Analysts: Professionals who want to expand their expertise to include machine learning, deep learning, and model deployment. or Software Engineers: Developers interested in applying programming skills to AI and machine learning projects. or Career Changers: Individuals from non-technical backgrounds with foundational Python knowledge, eager to transition into AI. or Graduate Students: Students in data science, computer science, or related fields wanting a practical, job-ready experience in AI engineering. or Tech Entrepreneurs: Founders and CTOs interested in understanding AI for building AI-driven products or managing AI teams.
Learn More About Artificial Intelligence Mastery: Complete AI Bootcamp 2025
What You Will Learn
- Master Python for AI: Write efficient Python code, essential for AI and ML programming tasks.
- Data Preprocessing Skills: Prepare, clean, and transform data to enhance model performance.
- Statistical Knowledge: Apply core statistics to understand data patterns and inform decisions.
- Build Machine Learning Models: Develop and fine-tune ML models for classification, regression, and clustering.
- Deep Learning Proficiency: Design and train neural networks, including CNNs and RNNs, for image and sequence tasks.
- Utilize Transfer Learning: Adapt pre-trained models to new tasks, saving time and resources.
- Deploy ML Models with APIs: Create scalable APIs to serve ML models in real-world applications.
- Containerize with Docker: Package models for portable deployment across environments.
- Monitor and Maintain Models: Track model performance, detect drift, and implement retraining pipelines.
- Complete ML Lifecycle: Master end-to-end AI project skills, from data to deployment and ongoing maintenance.
3. The AI Engineer Course 2025: Complete AI Engineer Bootcamp
Instructor: 365 Careers
Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs
Course Highlights:
- Rating: 4.57 ⭐ (1031 reviews)
- Students Enrolled: 11113
- Course Length: 85700 hours
- Number of Lectures: 358
- Number of Quizzes: 123
The AI Engineer Course 2025: Complete AI Engineer Bootcamp, has an average rating of 4.57, with 358 lectures, 123 quizzes, based on 1031 reviews, and has 11113 subscribers.
You will learn about The course provides the entire toolbox you need to become an AI Engineer Understand key Artificial Intelligence concepts and build a solid foundation Start coding in Python and learn how to use it for NLP and AI Impress interviewers by showing an understanding of the AI field Apply your skills to real-life business cases Harness the power of Large Language Models Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components Become familiar with Hugging Face and the AI tools it offers Use APIs and connect to powerful foundation models Utilize Transformers for advanced speech-to-text This course is ideal for individuals who are You should take this course if you want to become an AI Engineer or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills It is particularly useful for You should take this course if you want to become an AI Engineer or if you want to learn about the field or This course is for you if you want a great career or The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills.
Learn More About The AI Engineer Course 2025: Complete AI Engineer Bootcamp
What You Will Learn
- The course provides the entire toolbox you need to become an AI Engineer
- Understand key Artificial Intelligence concepts and build a solid foundation
- Start coding in Python and learn how to use it for NLP and AI
- Impress interviewers by showing an understanding of the AI field
- Apply your skills to real-life business cases
- Harness the power of Large Language Models
- Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components
- Become familiar with Hugging Face and the AI tools it offers
- Use APIs and connect to powerful foundation models
- Utilize Transformers for advanced speech-to-text
2. All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev
Instructor: Arnold Oberleiter
ChatGPT, Prompt Engineering, OpenAI API, GPTs, Chatbots, Automation, AI-Apps, Generative AI, Machine Learning, Copilot
Course Highlights:
- Rating: 4.66 ⭐ (1501 reviews)
- Students Enrolled: 13861
- Course Length: 133319 hours
- Number of Lectures: 405
- Number of Quizzes: 0
All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev, has an average rating of 4.66, with 405 lectures, based on 1501 reviews, and has 13861 subscribers.
You will learn about Introduction to AI: What Artificial Intelligence Is and What It Is Not Detailed prompt engineering for Midjourney, ChatGPT, Dall-E, Stable Diffusion, Adobe Firefly and more Understanding Learning Methods: Machine Learning, Deep Learning, Neural Networks Examples of AI: FSD, LLMs, Voice Assistants, Diffusion Models, Deepfakes & More Fundamentals of ChatGPT The Basics of AI All Functions of ChatGPT The History of AI from DeepMind to AlphaGO by IBM How LLMs (Large Language Models) Work Using the OpenAI Playground Working with the OpenAI API and Assistant API How Diffusion Models Work Building Your Own GPTs Building Assistants with OpenAI Building Simple Apps with the OpenAI API Supervised Learning and Reinforcement Learning Speech and Image Recognition Everything About GPTs and the GPT Store Creating a Builder Profile and Earning Money with GPTs Generating Leads with GPTs Integrating Zapier Actions into GPTs Incorporating GPTs into Websites with Flowsie and Node JS Overview of Programming Languages, Libraries, and Development Tools Using Google Colab Exploring GitHub and Huggingface Details About LLMs: Parameters, Prompt Engineering, Multimodality GPT Vision Training Your Own Diffusion Models Fine-Tuning of Diffusion Models [Loras] with Colab and Dreambooth Everything About Loras and Models in Stable Diffusion Creating Your Own Face with Stable Diffusion Using Diffusion Models like Midjourney, Adobe Firefly, and Dall-E Fine-Tuning of LLMs [GPT] in Google Colab Text-to-Speech with Elevenlabs and Whisper Creating Music Videos with Deforum Social Media Videos with Wrapfusion and Kaiber Deepfakes with WAV2Lip and Voice Cloning AI Avatars with Midjourney, Elevenlabs, and D-ID Ethical Concerns, Copyright, Privacy Issues Create content faster than ever before through effective prompt techniques Opportunities and risks of AI/ML like ChatGPT AI Voice Tools: Easily create AI-generated speech for any use case and even clone your own voice completely AI Video Tools: Create video presentations and quickly produce social media content AI Photo Tools: Add movement to images, edit pictures using inpainting and outpainting Combine AI tools for the best results with Upscaling and more Learn, improve, and debug code programming Programming your own games Monetizing your AI skills and learn how to make Money with AI Side Hustle Ideas and how to Sell ChatBots Building a AI Automation Agency Boosting productivity in all areas of your life SEO optimization of your content All parameters and modifiers in Leonardo and Midjourney This course is ideal for individuals who are This course is aimed at everyone who is interested in using AI tools like ChatGPT, regardless of their background. or To everyone who wants to learn something new or To entrepreneurs who want to become more efficient and save money or Private individuals who are interested in AI and want to build their own models. It is particularly useful for This course is aimed at everyone who is interested in using AI tools like ChatGPT, regardless of their background. or To everyone who wants to learn something new or To entrepreneurs who want to become more efficient and save money or Private individuals who are interested in AI and want to build their own models.
Learn More About All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev
What You Will Learn
- Introduction to AI: What Artificial Intelligence Is and What It Is Not
- Detailed prompt engineering for Midjourney, ChatGPT, Dall-E, Stable Diffusion, Adobe Firefly and more
- Understanding Learning Methods: Machine Learning, Deep Learning, Neural Networks
- Examples of AI: FSD, LLMs, Voice Assistants, Diffusion Models, Deepfakes & More
- Fundamentals of ChatGPT
- The Basics of AI
- All Functions of ChatGPT
- The History of AI from DeepMind to AlphaGO by IBM
- How LLMs (Large Language Models) Work
- Using the OpenAI Playground
- Working with the OpenAI API and Assistant API
- How Diffusion Models Work
- Building Your Own GPTs
- Building Assistants with OpenAI
- Building Simple Apps with the OpenAI API
- Supervised Learning and Reinforcement Learning
- Speech and Image Recognition
- Everything About GPTs and the GPT Store
- Creating a Builder Profile and Earning Money with GPTs
- Generating Leads with GPTs
- Integrating Zapier Actions into GPTs
- Incorporating GPTs into Websites with Flowsie and Node JS
- Overview of Programming Languages, Libraries, and Development Tools
- Using Google Colab
- Exploring GitHub and Huggingface
- Details About LLMs: Parameters, Prompt Engineering, Multimodality
- GPT Vision
- Training Your Own Diffusion Models
- Fine-Tuning of Diffusion Models [Loras] with Colab and Dreambooth
- Everything About Loras and Models in Stable Diffusion
- Creating Your Own Face with Stable Diffusion
- Using Diffusion Models like Midjourney, Adobe Firefly, and Dall-E
- Fine-Tuning of LLMs [GPT] in Google Colab
- Text-to-Speech with Elevenlabs and Whisper
- Creating Music Videos with Deforum
- Social Media Videos with Wrapfusion and Kaiber
- Deepfakes with WAV2Lip and Voice Cloning
- AI Avatars with Midjourney, Elevenlabs, and D-ID
- Ethical Concerns, Copyright, Privacy Issues
- Create content faster than ever before through effective prompt techniques
- Opportunities and risks of AI/ML like ChatGPT
- AI Voice Tools: Easily create AI-generated speech for any use case and even clone your own voice completely
- AI Video Tools: Create video presentations and quickly produce social media content
- AI Photo Tools: Add movement to images, edit pictures using inpainting and outpainting
- Combine AI tools for the best results with Upscaling and more
- Learn, improve, and debug code programming
- Programming your own games
- Monetizing your AI skills and learn how to make Money with AI
- Side Hustle Ideas and how to Sell ChatBots
- Building a AI Automation Agency
- Boosting productivity in all areas of your life
- SEO optimization of your content
- All parameters and modifiers in Leonardo and Midjourney
1. Ethical Generative AI: A Practical Guide for Professionals
Instructor: Dr. Seema Chokshi
Understand Generative AI, Navigate Ethical Issues, Apply Mitigation Techniques, and Implement Assessment Frameworks
Course Highlights:
- Rating: 5 ⭐ (6 reviews)
- Students Enrolled: 13
- Course Length: 4272 hours
- Number of Lectures: 13
- Number of Quizzes: 5
Ethical Generative AI: A Practical Guide for Professionals, has an average rating of 5, with 13 lectures, 5 quizzes, based on 6 reviews, and has 13 subscribers.
You will learn about Understand the fundamentals of Generative AI Models /tools Types of Ethical issues with Generative AI models/tools Learn to identify ethical issues when using Generative AI models/ tools Learn to successfully mitigate ethical issues when using Generative AI models/tools Learn the framework to assess the Ethical impact of an AI tool This course is ideal for individuals who are Business Professionals and leaders, Executives who want to become responsible users of Generative AI It is particularly useful for Business Professionals and leaders, Executives who want to become responsible users of Generative AI.
Learn More About Ethical Generative AI: A Practical Guide for Professionals
What You Will Learn
- Understand the fundamentals of Generative AI Models /tools
- Types of Ethical issues with Generative AI models/tools
- Learn to identify ethical issues when using Generative AI models/ tools
- Learn to successfully mitigate ethical issues when using Generative AI models/tools
- Learn the framework to assess the Ethical impact of an AI tool
Note: This post contains affiliate links. We may receive a commission for purchases made through these links.
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