| 1 - Introduction.mp4 | 26.4 MB | ||
| 10 - What is Deep Learning.mp4 | 36 MB | ||
| 11 - What is Natural Language Processing NLP.mp4 | 17.7 MB | ||
| 12 - What is Generative AI.mp4 | 33.5 MB | ||
| 13 - Perceptual Pillars of AI.mp4 | 31.5 MB | ||
| 14 - Whiteboard How Gen AI Works Gemini Example.mp4 | 33.3 MB | ||
| 15 - Section 12 Identify Generative AI Technology Stack.mp4 | 7.6 MB | ||
| 16 - Large Language Models LLMs and Transformers.mp4 | 23.9 MB | ||
| 17 - Whiteboard RetrievalAugmented Generation RAG.mp4 | 107.2 MB | ||
| 18 - AI Algorithms and Neural Networks.mp4 | 26.4 MB | ||
| 19 - Demonstration GenAI Tools.mp4 | 11.7 MB | ||
| 2 - What is the CSGAIP Certification about.mp4 | 17.7 MB | ||
| 20 - Key Cloud offerings AWS Bedrock Google Vertex AI Azure OpenAI.mp4 | 19.4 MB | ||
| 21 - Section 13 Data and Model Lifecycle Management.mp4 | 4.4 MB | ||
| 22 - SDLC and AI Applications.mp4 | 36.2 MB | ||
| 23 - Importance of Data to AI Applications.mp4 | 36.8 MB | ||
| 24 - Cloud Computing Shared Model.mp4 | 16.5 MB | ||
| 25 - Module Review Questions.mp4 | 5.5 MB | ||
| 26 - Module Two Overview.mp4 | 2.3 MB | ||
| 27 - Section 21 Prompt Engineering and Optimization.mp4 | 4 MB | ||
| 28 - What is Prompt Engineering.mp4 | 61.7 MB | ||
| 29 - What is Context Engineering.mp4 | 46.8 MB | ||
| 3 - Discussion Importance of an AI First Strategy for Enterprises.mp4 | 31 MB | ||
| 30 - Prompt Engineering vs Context Engineering.mp4 | 55.8 MB | ||
| 31 - Demonstration TaskGoal Clearly defining what you want the AI to do.mp4 | 16.2 MB | ||
| 32 - Demonstration TaskGoal Clearly defining what you want the AI to do.mp4 | 22 MB | ||
| 33 - Demonstration Context Providing relevant background information audience pu.mp4 | 25.9 MB | ||
| 34 - Demonstration Format Specifying the desired output structure.mp4 | 26.5 MB | ||
| 35 - Demonstration ToneStyle Guiding the AIs voice.mp4 | 32.7 MB | ||
| 36 - Demonstration ConstraintsLimitations Setting boundaries for the output.mp4 | 24 MB | ||
| 37 - Demonstration Clarity Specificity and Affirmative Directives.mp4 | 20.5 MB | ||
| 38 - Section 22 Demonstrate Advanced Prompting Strategies.mp4 | 2.6 MB | ||
| 39 - Demonstration Iterative refinement How to improve prompts based on outputs.mp4 | 61.6 MB | ||
| 4 - Module Overview.mp4 | 3.9 MB | ||
| 40 - Demonstration ZeroShot Prompting.mp4 | 7.9 MB | ||
| 41 - Demonstration Feedback Loops.mp4 | 10.4 MB | ||
| 42 - Demonstration Generate Content.mp4 | 18 MB | ||
| 43 - Course Closeout.mp4 | 25.9 MB | ||
| 5 - Section 11 AIML Foundations.mp4 | 4.6 MB | ||
| 6 - What is AIML.mp4 | 41.5 MB | ||
| 7 - What are the Machine Learning Types.mp4 | 103.1 MB | ||
| 8 - Compare and Contrasting AIML.mp4 | 26.7 MB | ||
| 9 - AI Categories Generative AI Predictive AI Agentic AI and others.mp4 | 111 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 45 total files | |||
Certified Strategic Generative AI Professional (CSGAIP)
https://WebToolTip.com
Published 11/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.25 GB | Duration: 3h 33m
Generative AI Mastery: From Concept to Corporate Impact.
What you'll learn
Differentiate between generative models (which create new data) and discriminative models (which classify existing data).
Identify and explain the practical purpose of key generative model architectures, including Large Language Models (LLMs), Diffusion Models, and Generative Adv
Apply a range of prompting techniques—from basic formats to detailed instructions—to optimize output and achieve specific, high-quality results from any gener
nstrate advanced prompting strategies, such as few-shot prompting, zero-shot prompting, and chain-of-thought prompting, to guide complex reasoning and dra
Select the most appropriate generative AI tools and platforms (APIs, open-source, or commercial services) by analyzing specific business needs and use cases.
Integrate generative AI into existing professional workflows to automate and enhance common functions like summarizing reports, drafting marketing copy, and c
Use generative AI effectively for data-driven tasks, turning complex raw information into clear, actionable insights and visualizations
Identify and address the paramount ethical considerations in AI use, including risks related to bias, fairness, and data privacy.
Address fundamental legal and intellectual property (IP) challenges related to the content created by generative AI models
Implement best practices and a practical framework for the safe, transparent, and responsible deployment of AI solutions within an organization.
Requirements
Basic understanding of ChatGPT, Gemini or CoPilot.
Access to Free Tier Cloud Computing Services
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