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Generative Ai Llm Engineer

A comprehensive guide for Generative Ai Llm Engineer

""1PREREQUISITES2DEEP LEARNING & NLP FUNDAMENTALS3THE TRANSFORMER ARCHITECTURE4LARGE LANGUAGE MODELS (LLMS) FOUNDATIONS5BUILDING LLM APPLICATIONS (LLMOPS)6SECURITY, SAFETY & ALIGNMENT7DEPLOYMENT, INFERENCE & OPTIMIZATION8MULTIMODAL AI & FUTURE TRENDSGenerative Ai Llm EngineerProgramming FundamentalsPython MasteryGeneratorsDecoratorsTypingConcurrency &AsynchronousProgrammingObject-OrientedProgrammingOOPData Structures &AlgorithmsVersion ControlGit & GitHubCommand Line & BashScriptingMathematical FoundationsLinear AlgebraVectorsMatricesTensorsMultivariable CalculusDerivativesGradientsProbability &StatisticsDistributionsBayes' TheoremInformation TheoryEntropyCross-EntropyOptimizationTechniquesGradient DescentAdamHardware & Compute BasicsGPU ArchitectureFundamentalsCUDA CoresTensor CoresMemory Hierarchy &BandwidthCompute-Bound vs.Memory-Bound WorkloadsTraditional Machine LearningSupervised vs.Unsupervised LearningScikit-Learn FrameworkEvaluation MetricsAccuracyPrecisionRecallF1Overfitting,Underfitting, andRegularizationDeep Learning BasicsArtificial NeuralNetworksANNsBackpropagation & LossFunctionsActivation FunctionsReLUGELUSwiGLUOptimizers &SchedulersAdamWCosine AnnealingDeep LearningFrameworksPyTorchJAXTraditional Natural Language ProcessingText PreprocessingTokenizationStemmingLemmatizationBag of Words & TF-IDFWord EmbeddingsWord2VecGloVeSubword TokenizationBPEWordPieceSentencePieceTiktokenSequence-to-Sequence ModelsEncoder-DecoderArchitectureRecurrent NeuralNetworks (RNNs) &LSTMsThe AttentionMechanismBahdanau & LuongTransformer AnatomySelf-Attention &Multi-Head AttentionAdvanced AttentionMQAGQAFlashAttentionPositional EncodingAbsoluteRelativeRoPEALiBiLayer NormalizationPost-NormPre-NormRMSNormFeed-Forward NeuralNetworksSwiGLUTransformer VariantsEncoder-Only ModelsBERTRoBERTaDecoder-Only ModelsGPT SeriesLlamaMistralEncoder-Decoder ModelsT5BARTMixture of Experts(MoE) ArchitecturePre-trainingSelf-SupervisedLearning PrinciplesCausal LanguageModelingNext-Token PredictionMasked LanguageModelingMLMData Curation,Deduplication, and PIIScrubbingScaling Laws &Compute-OptimalTrainingChinchillaDistributed TrainingDataTensorPipeline ParallelismFSDPDeepSpeedAlignment & Fine-TuningSupervised Fine-TuningSFTInstruction TuningSynthetic DataGenerationSelf-InstructEvol-InstructReinforcement Learningfrom Human FeedbackRLHFDirect PreferenceOptimization (DPO),ORPO, & KTOConstitutional AI &RLAIFParameter-Efficient Fine-Tuning (PEFT)LoRA (Low-RankAdaptation) & DoRAQLoRAQuantized LoRAPrompt Tuning & PrefixTuningAdapters & PiSSAPrompt EngineeringZero-Shot, One-Shot,and Few-Shot PromptingChain-of-Thought (CoT)PromptingTree of Thoughts (ToT)& Graph of ThoughtsGoTSystem Prompts,Framing, and PersonaDefinitionFrameworks & OrchestrationLangChainChainsPromptsOutput ParsersLlamaIndexData ConnectorsIndicesHaystackPipelinesNodesDSPyProgramming &Compiling PromptsRetrieval-Augmented Generation (RAG)Naive RAG vs. AdvancedRAG ArchitectureDocument Loaders andParsersChunking StrategiesFixed-sizeSemanticRecursiveAgenticVector EmbeddingsOpenAIBGENomicVoyageVector DatabasesPineconeMilvusChromaDBQdrantWeaviateRetrieval StrategiesBM25Dense RetrievalHybrid SearchQuery Transformation(HyDE, Multi-Query) &RoutingRerankingCross-EncodersCohere RerankGraphRAG & KnowledgeGraphsAdvanced RAG ParadigmsSelf-RAGCRAGContext CompressionLLMLinguaAgents and Tool CallingReAct (Reasoning andActing) FrameworkFunction Calling & APIIntegrationSemantic RoutingMulti-Agent SystemsAutoGenCrewAILangGraphMemory ManagementShort-termLong-termEntity MemoryPlan-and-ExecuteArchitecturesTool Creation andExecution SandboxesEvaluation & ObservabilityBenchmarks &LeaderboardsMMLUHumanEvalMT-BenchChatbot ArenaEvaluating GenerativeOutputsBLEUROUGEBERTScoreLLM-as-a-JudgeG-EvalPrometheusRAG EvaluationFrameworksRAGASTruLensTracing &ObservabilityLangSmithPhoenixLangfuseA/B Testing and ShadowDeploymentsModel Safety & EthicsBias, Fairness, andToxicityHallucinations &GroundingRed Teaming &Vulnerability ScanningMachine Unlearning &Copyright MitigationAdversarial Attacks & DefensesPrompt Injection &JailbreakingData PoisoningOutput GuardrailsNeMo GuardrailsLlama GuardGuardrails AIDefensive Prompting &Input ValidationModel Inference & ServingContinuous Batching &PagedAttentionvLLM & SGLangText GenerationInferenceTGITensorRT-LLMLocal InferenceOllamaLlama.cppMLXModel HubsHugging FaceModelScopeOptimization TechniquesQuantizationGGUFAWQGPTQEXL2SmoothQuantKV Cache Optimization& Prompt CachingSpeculative DecodingContext LengthExtensionYaRNALiBiModel Pruning andDistillationCloud & Production DeploymentDeploying on CloudProvidersAWS BedrockAzure OpenAIGCP VertexServerless GPUPlatformsRunPodModalReplicateBasetenAPI Design, RateLimiting, and CachingEnterprise ComplianceSOC2GDPRHIPAAVision-Language Models (VLMs)ContrastiveLanguage-ImagePretrainingCLIPLLaVA and MultimodalLLM ArchitecturesDocument AI andLayoutLMAudio & Generation ModelsSpeech-to-TextWhisperText-to-SpeechTTSImage & VideoGenerationStable DiffusionMidjourneySoraEmerging TrendsSmall Language Models(SLMs) and Edge AIContinuous Learning inLLMsState Space ModelsMambaJambaRWKVAutonomous AI SoftwareEngineersDevin