What you'll get
- 22+ Hours
- 5 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
Synopsis
- Career-focused Generative AI program covering AI fundamentals to advanced applications
- Learn Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI
- Build, train, and deploy AI models using AWS Cloud
- Apply AI to real-world business use cases across industries
- Focus on ethical AI, responsible deployment, and hallucination reduction
- Suitable for both technical and non-technical learners.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| AI Fundamentals and Core Concepts | 5h 41m | ✔ | View Curriculum |
| Advanced AI and Technologies | 4h 18m | ✔ | View Curriculum |
| Generative AI and Applications | 9h 02m | ✔ | View Curriculum |
| Research, Performance, and Writing with AI | 2h 39m | ✔ | View Curriculum |
| Ethical and Future AI Considerations | 2h 46m | ✔ | View Curriculum |
Description
This Generative AI Training provides a deep understanding of Artificial Intelligence, progressing from core AI concepts to specialized domains such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Generative AI. Learners build, train, optimize, and deploy AI models in real-world production environments.
The curriculum emphasizes practical business applications, including finance analytics, market forecasting, recruitment automation, customer insights, and personal brand enhancement. Ethical AI, responsible deployment, and techniques to reduce hallucination are integrated throughout the course to ensure trustworthy and scalable AI solutions.
Goals
- Build a strong foundation in AI and Generative AI
- Enable learners to translate real-world business problems into AI solutions
- Develop industry-ready skills for designing, deploying, and scaling AI systems
- Promote ethical, responsible, and risk-aware AI development.
Objectives
By the end of this Generative AI Training, learners will be able to:
- Understand core AI concepts and model architectures
- Develop and train Machine Learning and Deep Learning models
- Apply NLP techniques for text understanding and content generation
- Use Computer Vision methods to analyze and interpret visual data
- Build and deploy AI applications using AWS Cloud
- Reduce AI hallucinations and improve output reliability
- Implement responsible AI practices aligned with organizational needs
- Apply AI solutions across multiple industries and business functions.
Highlights
- End-to-end AI learning path in a single unified track
- Coverage of Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI
- Practical techniques to minimize AI hallucinations
- Real-world industry use cases: finance, hiring, marketing, analytics, and automation
- AWS-based AI deployment and production workflows
- Focus on ethical AI, governance, and risk management
- Designed for both technical and non-technical professionals.
Requirements
To join the Generative AI Training, learners should have:
- Basic computer proficiency
- High-school-level mathematics knowledge (recommended)
- Interest in Artificial Intelligence and real-world applications
- Internet access for cloud-based platforms such as AWS.
Target Audience
This Generative AI Training is ideal for:
- Students and aspiring AI professionals
- Business leaders and decision-makers
- Data analysts and technology enthusiasts
- Researchers, educators, and content creators
- Entrepreneurs exploring AI-driven solutions.
FAQ
Q1. Is prior coding experience required?
No. The course covers technical concepts while remaining accessible to beginners and business professionals alike.
Q2. Does the course include hands-on projects?
Yes. Learners work with real-world use cases and AWS-based AI deployments to gain practical experience.
Q3. Will this course cover Generative AI tools and models?
Yes. The course dives into Generative AI architectures, content generation techniques, and reliability improvements.
Q4. Is the course suitable for business leaders?
Absolutely. Strategic AI adoption, decision-making use cases, and ethical considerations are key components.
Q5. Does the course address ethical and responsible AI?
Yes. We integrate responsible AI principles, risk awareness, and ethical guidelines throughout the curriculum.
Career Benefits
- Enhanced career opportunities in AI, Data Science, and Analytics
- Ability to design and deploy AI solutions aligned with business goals
- Industry-relevant skills in Generative AI and cloud-based AI systems
- Competitive advantage in roles across finance, marketing, HR, and technology
- Strong foundation for advanced AI roles or entrepreneurial ventures.