Udemy - AI Foundations For Decision Makers - From Zero To LLMs

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 2.6 GB
  • Uploaded By freecoursewb
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  • Last checked 1 day ago
  • Date uploaded 9 months ago
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Infohash : CAE7B6F089BE1A9DF576C9D415BDBC8AE293DF22



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.

Files:

[ WebToolTip.com ] Udemy - AI Foundations For Decision Makers - From Zero To LLMs
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 - Introduction.mp4 (90.9 MB)
    • 2 - Who is this course for.mp4 (30.4 MB)
    • 3 - Course Outline.mp4 (90.5 MB)
    2 - Fundamentals of Machine Learning and AI Introduction to AI and Machine Learning
    • 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 (0.0 KB)
    • 16 - Internet archive.txt
    • 16 - Kaggle.txt (0.0 KB)
    • 16 - Key AIML Topics Key Data Sources.mp4 (15.9 MB)
    • 16 - Open Data on AWS.txt (0.1 KB)
    • 16 - OpenDataMonitor.txt (0.0 KB)
    • 16 - Quandl.txt (0.0 KB)
    • 16 - UC Irvine Machine Learning Repository.txt (0.0 KB)
    • 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)
    • 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 (0.1 KB)
    • 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 (1.0 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)
    • 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)
    • 4 - What is AI.mp4 (65.0 MB)
    • 5 - Ebook-SamGhosh-AI-Foundations-for-Decision-Makers.pdf (4.9 MB)
    • 5 - Narrow AI vs Broad AI.mp4 (21.7 MB)
    • 6 - How does ML differ from traditional software.mp4 (20.2 MB)
    • 7 - Must Read Papers for Data Science ML and DL.txt (0.0 KB)
    • 7 - Types of Machine Learning.mp4 (55.7 MB)
    • 8 - Features Data as the foundation Features Labels and Datasets.mp4 (19.4 MB)
    • 9 - Labels Data as the foundation Features Labels and Datasets.mp4 (24.4 MB)
    • 3 - Fundamentals of Large Language Models
      • 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)
      • 40 - Scaling Laws.mp4 (49.0 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 (1.0 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)
      • 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 (4.0 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)
      • 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)
      • 70 - Command R Cohere Other Enterprise LLMs.mp4 (21.9 MB)
      • 71 - Key Selection Factors for LLMs.mp4 (20.3 MB)
      • 72 - BIGBenchHard.txt (0.0 KB)
      • 72 - BIGbench.txt (0.0 KB)
      • 72 - GLUE.txt (0.0 KB)
      • 72 - GSM8K.txt (0.0 KB)
      • 72 - HumanEval.txt (0.0 KB)
      • 72 - LLM Performance Benchmarks.mp4 (19.2 MB)
      • 72 - MATH.txt (0.0 KB)
      • 72 - MMLU.txt (0.0 KB)
      • 72 - SQuAD V2.txt (0.0 KB)
      • 72 - SQuAD.txt (0.0 KB)
      • 72 - superGLUE.txt (0.0 KB)
      • 73 - AGIEval.txt (0.0 KB)
      • 73 - Chatbot Arena.txt (0.0 KB)
      • 73 - Codebench.txt (0.0 KB)
      • 73 - HELM.txt (0.0 KB)
      • 73 - LLM Leaderboards.mp4 (20.0 MB)
      • 73 - MTBench.txt (0.0 KB)
      • 73 - Open LLM Leaderboard.txt (0.1 KB)
      • 73 - TruthfulQA.txt (0.0 KB)
      • 74 - Accenture AI.txt (0.0 KB)
      • 74 - AiTuning.txt (0.0 KB)
      • 74 - IntelligentMind.txt (0.0 KB)
      • 74 - LLM Deployment Strategies.mp4 (35.6 MB)
      • 74 - Vaidik.txt (0.0 KB)
      • 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)
      4 - Understanding the Agent Economy
      • 76 - Review.mp4 (31.0 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)
      • 80 - AutoGPT.txt (0.0 KB)
      • 80 - CodeAgent.pdf (1.1 MB)
      • 80 - LangChain.txt (0.0 KB)
      • 80 - Major Examples of AI Agents.mp4 (16.7 MB)
      • 80 - MusicLM-Generating-Music-From-Text.pdf (835.6 KB)
      • 80 - OpenDevin.txt (0.0 KB)
      • 80 - The AI Scientist.txt (0.0 KB)
      • 80 - Voyager.txt (0.0 KB)
      • 80 - microsoftUFO.txt (0.0 KB)
      • 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 (0.1 KB)
      • 83 - The Agent Economy.mp4 (28.3 MB)
      • 84 - A-Taxonomy-of-AgentOps-for-Enabling-Observability-of-Foundation-Model-based-Agents.pdf (510.0 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 (34.0 MB)
      • 88 - Thanks.mp4 (18.3 MB)
      • Bonus Resources.txt (0.1 KB)

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