| 1 - Introduction.mp4 | 90.9 MB | ||
| 10 - Datasets Data as the foundation Features Labels and Datasets.mp4 | 18.8 MB | ||
| 11 - Training vs Inference How do AI models learn and make predictions.mp4 | 30.4 MB | ||
| 12 - Common challenges Overfitting.mp4 | 24.3 MB | ||
| 13 - Common challenges Bias.mp4 | 7.4 MB | ||
| 14 - Common challenges Generalization.mp4 | 13.4 MB | ||
| 15 - Key AIML Topics Feature Engineering.mp4 | 45.4 MB | ||
| 16 - Google dataset search.txt | 0 B | ||
| 16 - Kaggle.txt | 0 B | ||
| 16 - Key AIML Topics Key Data Sources.mp4 | 15.9 MB | ||
| 16 - Open Data on AWS.txt | 102.4 B | ||
| 16 - OpenDataMonitor.txt | 0 B | ||
| 16 - Quandl.txt | 0 B | ||
| 16 - UC Irvine Machine Learning Repository.txt | 0 B | ||
| 17 - Key AIML Topics Model Selection Different types of ML Models.mp4 | 31.8 MB | ||
| 18 - Key AIML Topics Model Selection How to select a suitable model.mp4 | 20.4 MB | ||
| 19 - Key AIML Topics Model Evaluation Validation and CrossValidation.mp4 | 38.4 MB | ||
| 2 - Who is this course for.mp4 | 30.4 MB | ||
| 20 - A-REVIEW-ON-EVALUATION-METRICS-FOR-DATA-CLASSIFICATION-EVALUATIONS.pdf | 160.5 KB | ||
| 20 - Key AIML Topics Evaluating Model Performance.mp4 | 29.6 MB | ||
| 20 - Model-Evaluation-Model-Selection-and-Algorithm-Selection-in-Machine-Learning.pdf | 1.9 MB | ||
| 20 - The-Relationship-Between-Precision-Recall-and-ROC-Curves.pdf | 138.2 KB | ||
| 21 - Key AIML Topics Hyperparameters.mp4 | 24.8 MB | ||
| 22 - Dropout-A-Simple-Way-to-Prevent-Neural-Networks-from-Overfitting.pdf | 2.7 MB | ||
| 22 - Key AIML Topics Model Regularization.mp4 | 13.4 MB | ||
| 23 - Awesome Deep Learning Related Survey Papers.txt | 102.4 B | ||
| 23 - Deep Learning and Artificial Neural Networks What are Artificial Neural Network.mp4 | 67.2 MB | ||
| 24 - Forward Propagation Backpropagation Gradient Descent.mp4 | 79.3 MB | ||
| 25 - A-survey-on-modern-trainable-activation-functions.pdf | 1 MB | ||
| 25 - Activation Functions.mp4 | 71.4 MB | ||
| 25 - Activation-Functions-in-Deep-Learning-A-Comprehensive-Survey-and-Benchmark.pdf | 836.5 KB | ||
| 26 - A-Survey-of-Optimization-Methods-from-a-Machine-Learning-Perspective.pdf | 564.1 KB | ||
| 26 - Optimization Algorithms.mp4 | 68.1 MB | ||
| 27 - Intro to NLP Text Processing in NLP.mp4 | 29.4 MB | ||
| 28 - Applications of NLP.mp4 | 7.8 MB | ||
| 29 - Core NLP Tasks.mp4 | 25.1 MB | ||
| 3 - Course Outline.mp4 | 90.5 MB | ||
| 30 - NLP Approaches.mp4 | 22.4 MB | ||
| 31 - Traditional Language Models.mp4 | 26.1 MB | ||
| 32 - Challenges in NLP.mp4 | 19.4 MB | ||
| 33 - A-Neural-Probabilistic-Language-Model.pdf | 136.8 KB | ||
| 33 - A-STATISTICAL-APPROACH-TO-MACHINE-TRANSLATION.pdf | 658.2 KB | ||
| 33 - Perplexity.mp4 | 24.6 MB | ||
| 34 - EncodingDecoding Architecture.mp4 | 22.4 MB | ||
| 35 - Review.mp4 | 36.8 MB | ||
| 36 - What is Attention.mp4 | 18.4 MB | ||
| 37 - Understanding Transformers The shift from RNNs CNNs to Transformers.mp4 | 53.1 MB | ||
| 38 - Attention Is All You Need How selfattention enables LLMs.mp4 | 65.6 MB | ||
| 38 - attentionisall.pdf | 2.1 MB | ||
| 39 - SelfAttention and CrossAttention.mp4 | 59.1 MB | ||
| 4 - What is AI.mp4 | 65 MB | ||
| 40 - Scaling Laws.mp4 | 49 MB | ||
| 40 - Scaling-Laws-for-Neural-Language-Models.pdf | 2.4 MB | ||
| 40 - Training-Compute-Optimal-Large-Language-Models.pdf | 5.7 MB | ||
| 41 - How LLMs learn and adapt.mp4 | 28.5 MB | ||
| 41 - Large-Language-Models-A-Survey.pdf | 4.7 MB | ||
| 42 - Types of Pretraining.mp4 | 17.7 MB | ||
| 43 - Selfsupervised Learning.mp4 | 43.2 MB | ||
| 44 - LLM Model Architectures.mp4 | 80.4 MB | ||
| 45 - Model Size and Capabilities.mp4 | 21.4 MB | ||
| 46 - Finetuning Fundamentals.mp4 | 12.8 MB | ||
| 46 - Instruction-Tuning-with-GPT-4.pdf | 1.5 MB | ||
| 46 - Prefix-Tuning-Optimizing-Continuous-Prompts-for-Generation.pdf | 1.5 MB | ||
| 47 - Adapters-A-Unified-Library-for-Parameter-Efficient-and-Modular-Transfer-Learning.pdf | 1.4 MB | ||
| 47 - LoRA-Low-Rank-Adaptation-of-Large-Language-Models.pdf | 1.5 MB | ||
| 47 - ParameterEfficient FineTuning PEFT.mp4 | 28.5 MB | ||
| 47 - QLoRA-Efficient-Finetuning-of-Quantized-LLMs.pdf | 1 MB | ||
| 48 - PostTraining Fundamentals.mp4 | 11.4 MB | ||
| 48 - RLAIF-vs.RLHF-Scaling-Reinforcement-Learning-from-Human-Feedback-with-AI-Feedback.pdf | 2.4 MB | ||
| 49 - Pre-train-Prompt-and-Predict-A-Systematic-Survey-of-Prompting-Methods-in-Natural-Language-Processing.pdf | 11.8 MB | ||
| 49 - Ways to interact with LLMs.mp4 | 63.2 MB | ||
| 5 - Ebook-SamGhosh-AI-Foundations-for-Decision-Makers.pdf | 4.9 MB | ||
| 5 - Narrow AI vs Broad AI.mp4 | 21.7 MB | ||
| 50 - Zeroshot Prompting.mp4 | 6.2 MB | ||
| 51 - Chain-of-Thought-Prompting-Elicits-Reasoning-in-Large-Language-Models.pdf | 870.9 KB | ||
| 51 - ChainofThought CoT Reasoning.mp4 | 5.6 MB | ||
| 52 - Zeroshot ChainofThought CoT.mp4 | 2.6 MB | ||
| 53 - Fewshot Prompting.mp4 | 3.8 MB | ||
| 53 - Language-Models-are-Few-Shot-Learners.pdf | 6.5 MB | ||
| 54 - Fewshot Prompting CoT.mp4 | 2.8 MB | ||
| 55 - DemonstrateSearchPredict.mp4 | 4.4 MB | ||
| 56 - Interleaved Retrieval guided by ChainofThought IRCoT.mp4 | 4 MB | ||
| 57 - SelfConsistency and Tree of Thoughts ToT.mp4 | 23.3 MB | ||
| 58 - Retrieval-Augmented-Generation-for-Knowledge-Intensive-NLP-Tasks.pdf | 864.6 KB | ||
| 58 - Retrieval-Augmented-Generation-for-Large-Language-Models-A-Survey.pdf | 1.6 MB | ||
| 58 - RetrievalAugmented Generation RAG.mp4 | 28.9 MB | ||
| 59 - AI Agents Autonomous Reasoning.mp4 | 39.9 MB | ||
| 6 - How does ML differ from traditional software.mp4 | 20.2 MB | ||
| 60 - OpenSource vs Proprietary LLMs.mp4 | 26.1 MB | ||
| 61 - GPT Series OpenAI.mp4 | 18.3 MB | ||
| 62 - BERT RoBERTa Google Meta.mp4 | 14.2 MB | ||
| 63 - T5 UL2 Google.mp4 | 22.8 MB | ||
| 64 - Claude Anthropic.mp4 | 15.7 MB | ||
| 65 - LLaMA Meta.mp4 | 11.8 MB | ||
| 66 - Mistral Mixtral.mp4 | 13.2 MB | ||
| 67 - Gemini Google DeepMind.mp4 | 20.5 MB | ||
| 68 - DeepSeek r1.mp4 | 6.9 MB | ||
| 69 - Grok xAI.mp4 | 11.7 MB | ||
| 7 - Must Read Papers for Data Science ML and DL.txt | 0 B | ||
| 7 - Types of Machine Learning.mp4 | 55.7 MB | ||
| 70 - Command R Cohere Other Enterprise LLMs.mp4 | 21.9 MB | ||
| 71 - Key Selection Factors for LLMs.mp4 | 20.3 MB | ||
| 72 - BIGBenchHard.txt | 0 B | ||
| 72 - BIGbench.txt | 0 B | ||
| 72 - GLUE.txt | 0 B | ||
| 72 - GSM8K.txt | 0 B | ||
| 72 - HumanEval.txt | 0 B | ||
| 72 - LLM Performance Benchmarks.mp4 | 19.2 MB | ||
| 72 - MATH.txt | 0 B | ||
| 72 - MMLU.txt | 0 B | ||
| 72 - SQuAD V2.txt | 0 B | ||
| 72 - SQuAD.txt | 0 B | ||
| 72 - superGLUE.txt | 0 B | ||
| 73 - AGIEval.txt | 0 B | ||
| 73 - Chatbot Arena.txt | 0 B | ||
| 73 - Codebench.txt | 0 B | ||
| 73 - HELM.txt | 0 B | ||
| 73 - LLM Leaderboards.mp4 | 20 MB | ||
| 73 - MTBench.txt | 0 B | ||
| 73 - Open LLM Leaderboard.txt | 102.4 B | ||
| 73 - TruthfulQA.txt | 0 B | ||
| 74 - Accenture AI.txt | 0 B | ||
| 74 - AiTuning.txt | 0 B | ||
| 74 - IntelligentMind.txt | 0 B | ||
| 74 - LLM Deployment Strategies.mp4 | 35.6 MB | ||
| 74 - Vaidik.txt | 0 B | ||
| 75 - A-Comprehensive-Analysis-of-Memorization-in-Large-Language-Models.pdf | 1.3 MB | ||
| 75 - A-Review-of-Current-Trends-Techniques-and-Challenges-in-Large-Language-Models-LLMs.pdf | 533.4 KB | ||
| 75 - A-Survey-on-Hallucination-in-Large-Language-Models-Principles-Taxonomy-Challenges-and-Open-Questions.pdf | 1.5 MB | ||
| 75 - Demystifying-Verbatim-Memorization-in-Large-Language-Models.pdf | 3.3 MB | ||
| 75 - Large-Language-Models-A-Comprehensive-Survey-of-its-Applications-Challenges-Limitations-and-Future-Prospects.pdf | 6.2 MB | ||
| 75 - Technical Challenges in LLMs.mp4 | 28.6 MB | ||
| 76 - Review.mp4 | 31 MB | ||
| 77 - What are AI Agents.mp4 | 13.2 MB | ||
| 78 - Traditional Automation to Autonomous Agents.mp4 | 4.9 MB | ||
| 79 - Why do Agents Matter in the AIDriven Future.mp4 | 10.9 MB | ||
| 8 - Features Data as the foundation Features Labels and Datasets.mp4 | 19.4 MB | ||
| 80 - AutoGPT.txt | 0 B | ||
| 80 - CodeAgent.pdf | 1.1 MB | ||
| 80 - LangChain.txt | 0 B | ||
| 80 - Major Examples of AI Agents.mp4 | 16.7 MB | ||
| 80 - MusicLM-Generating-Music-From-Text.pdf | 835.6 KB | ||
| 80 - OpenDevin.txt | 0 B | ||
| 80 - The AI Scientist.txt | 0 B | ||
| 80 - Voyager.txt | 0 B | ||
| 80 - microsoftUFO.txt | 0 B | ||
| 81 - The-AI-Scientist-Towards-Fully-Automated-Open-Ended-Scientific-Discovery.pdf | 11.2 MB | ||
| 81 - Types of AI Agents.mp4 | 17.7 MB | ||
| 82 - How do AI Agents Work.mp4 | 51.2 MB | ||
| 83 - AutoGen.txt | 102.4 B | ||
| 83 - The Agent Economy.mp4 | 28.3 MB | ||
| 84 - A-Taxonomy-of-AgentOps-for-Enabling-Observability-of-Foundation-Model-based-Agents.pdf | 510 KB | ||
| 84 - AIOS-LLM-Agent-Operating-System.pdf | 1.3 MB | ||
| 84 - AgentOps.mp4 | 24.8 MB | ||
| 85 - Use Cases of AI Agents.mp4 | 12.3 MB | ||
| 86 - Ethical and Practical Challenges of AI Agents.mp4 | 52.5 MB | ||
| 87 - The Convergence of LLMs MultiModal AI and Automation.mp4 | 34 MB | ||
| 88 - Thanks.mp4 | 18.3 MB | ||
| 9 - Labels Data as the foundation Features Labels and Datasets.mp4 | 24.4 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 161 total files | |||
AI Foundations For Decision Makers: From Zero To LLMs
https://WebToolTip.com
Published 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.55 GB | Duration: 6h 21m
Becoming an AI-First Decision Maker
What you'll learn
Develop an AI-First Strategy - Formulate a business strategy that leverages AI and LLMs for sustainable competitive advantage.
Evaluate & Select AI Models - Assess different LLMs based on performance, cost, compliance, and business needs without requiring a technical background.
Bridge the Gap Between AI & Business - Effectively communicate with technical teams, hire AI talent, and make informed decisions on AI adoption.
Understand AI Agents & Automation - Analyze how AI-powered agents are reshaping workflows, business models, and industry dynamics.
Identify AI Risks & Challenges - Recognize potential pitfalls such as hallucinations, bias, and computational costs, and develop risk-mitigation strategies.
Requirements
No programming experience is required. Some exposure to math can be helpful.
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| 1.8 GB | freecoursewb | 1 week | 8 | 6 | |
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Udemy - IMRaD-Q1 Paper Writing and Publishing with ChatGPT and AI '26 Posted by
freecoursewb in Other
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| 3.2 GB | freecoursewb | 2 weeks | 4 | 12 | |
| 3.3 GB | freecoursewb | 2 weeks | 18 | 8 | |
| 1.1 GB | freecoursewb | 2 weeks | 0 | 0 |
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