From Traditional AI to Generative AI
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Generative Artificial Intelligence AI-102
Generative AI and Large Language Models
A Clear Guide to Foundation Models, Transformers, Tokens, Embeddings, and Machine-Generated Content
A structured ten-module course explaining how generative AI and large language models work and how they should be evaluated, controlled and used responsibly.
US$145
An electronic First BCI University Certificate of Completion in PDF format is included after successful completion.
AI-102
Course overview
AI-102 develops practical literacy in generative artificial intelligence and large language models without requiring advanced mathematics or programming.
Students examine foundation models, tokenization, embeddings, transformers, attention, model training, multimodal generation, prompting, retrieval, fine-tuning, agents, evaluation, security and responsible deployment.
The course emphasizes that fluent output is not automatically accurate. Learners practice defining evidence requirements, testing realistic cases and preserving accountable human review.
Learning objectives
What you will learn
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01
Explain the difference between predictive and generative AI.
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02
Define foundation models and large language models.
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03
Describe tokens, context windows and embeddings.
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04
Explain transformers and attention conceptually.
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05
Describe pretraining, post-training, fine-tuning and alignment.
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06
Compare text, image, audio, video and code generation.
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07
Use prompting, retrieval and tool integration appropriately.
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08
Identify hallucination, bias, security and privacy risks.
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09
Evaluate models using representative task-specific evidence.
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10
Design a responsible generative AI adoption plan.
Ten structured modules
Course curriculum
Foundation Models and Large Language Models
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Tokens, Context Windows, and Embeddings
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Transformers, Attention, and Model Architecture
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
How Generative Models Learn
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Generating Text, Images, Audio, Video, and Code
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Prompting, Retrieval, Fine-Tuning, and AI Agents
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Hallucinations, Bias, Security, and Reliability
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Evaluating and Selecting Generative AI Models
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
The Future of Generative AI and Responsible Human Use
A structured lesson with objectives, explanations, key terms, case study, applied exercise and ten-question knowledge check.
Official recommended coursebook
First BCI University Generative AI and Large Language Models
A Clear Guide to Foundation Models, Transformers, Tokens, Embeddings, and Machine-Generated Content
- Author
- Konstantin Titov
The official recommended coursebook follows the ten-module AI-102 curriculum with expanded explanations, examples, review questions and applied activities.
Available now as a secure downloadable eBook for US$12.99.
BUY THIS BOOK — US$12.99Successful completion
Assessment and completion
Assessment components
- Ten module knowledge checks with ten questions each.
- Applied exercise and case-study analysis in every module.
- Course progress recorded in the student learning environment.
- Final assessment covering the complete AI-102 curriculum.
Completion requirements
- Study all ten modules.
- Achieve at least 70% in every module knowledge check.
- Complete required applied learning activities.
- Pass the final assessment.
AI-102 Enrollment
Begin Generative AI and Large Language Models
US$145
Secure online access includes all ten modules, knowledge checks, progress tracking, final assessment and an electronic Certificate of Completion after successful completion.
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