Large Language Model Operations (LLMOps)

Master Large Language Model Operations on Azure

• Unlock Azure's full potential for deploying & optimizing Large Language Models (LLMs)
• Build robust LLM applications leveraging Azure Machine Learning & OpenAI Service
• Implement architectural patterns & GitHub Actions workflows for streamlined MLOps

Course Highlights:

• Explore Azure AI services and LLM capabilities
• Mitigate risks with foundational strategies
• Leverage Azure ML for model deployment & management
• Optimize GPU quotas for performance & cost-efficiency
• Craft advanced queries for enriched LLM interactions
• Implement Semantic Kernel for enhanced query results
• Dive into architectural patterns like RAG for scalable architectures
• Build end-to-end LLM apps using Azure services & GitHub Actions

Ideal for data professionals, AI enthusiasts & Azure users looking to harness cutting-edge language AI capabilities. Gain practical MLOps skills through tailored modules & hands-on projects.

Master deploying generative AI models like GPT on AWS through hands-on labs. Learn architecture selection, cost optimization, monitoring, CI/CD pipelines, and compliance best practices. Gain skills in operationalizing LLMs using Amazon Bedrock, auto-scaling, spot instances, and differential privacy techniques. Ideal for ML engineers, data scientists, and technical leaders.

Course Highlights:

• Choose optimal LLM architectures for your applications
• Optimize cost, performance and scalability with auto-scaling and orchestration
• Monitor LLM metrics and continuously improve model quality
• Build secure CI/CD pipelines to train, deploy and update LLMs
• Ensure regulatory compliance via differential privacy and controlled rollouts
• Real-world, hands-on training for production-ready generative AI

Unlock the power of large language models on AWS. Master operationalization using cloud-native services through this comprehensive, practical training program.

Master Data Engineering on Databricks Lakehouse Platform

• Learn Databricks architecture, cluster management & notebook analysis
• Build reliable ETL pipelines with Delta Lake for data transformation
• Implement advanced data processing techniques with Apache Spark

Course Highlights:

• Create & scale Databricks clusters for workloads
• Load data from diverse sources into notebooks
• Explore, visualize & profile datasets with notebooks
• Version control & share notebooks via Git integration
• Read & ingest data in various file formats
• Transform data with SQL & DataFrame operations
• Handle complex data types like arrays, structs, timestamps
• Deduplicate, join & flatten nested data structures
• Identify & fix data quality issues with UDFs
• Load cleansed data into Delta Lake for reliability
• Build production-ready pipelines with Delta Live Tables
• Schedule & monitor workloads using Databricks Jobs
• Secure data access with Unity Catalog

Gain comprehensive skills in data engineering on Databricks through hands-on labs, real-world projects and best practices for the modern data lakehouse.

Experience Open Source Large Language Models (LLMs)

• Master cutting-edge LLM architectures like Transformers through hands-on labs
• Fine-tune models on your data with SkyPilot's scalable training platform
• Deploy efficiently with model servers like LoRAX and vLLM

Explore the Open Source LLM Ecosystem:

• Gain in-depth understanding of how LLMs work under the hood
• Run pre-trained models like Code Llama, Mistral & Stable Diffusion
• Discover advanced architectures like Sparse Expert Models
• Launch cloud GPU instances for accelerated compute

Guided LLM Project:

• Fine-tune LLaMA, Mistral or other LLMs on your custom dataset
• Leverage SkyPilot to scale training across cloud providers
• Containerize your fine-tuned model for production deployment
• Serve models efficiently with LoRAX, vLLM and other open servers
• Build powerful AI solutions leveraging state-of-the-art open source language models. Gain practical LLMOps skills through code-first learning.

Master Scalable Data Engineering with Cutting-Edge Tools

• Learn to handle massive datasets efficiently with this advanced course
• Gain practical expertise in scaling data systems using modern technologies
• Ideal for data scientists, engineers & professionals with data handling experience

Course Highlights:

• Leverage Celery & RabbitMQ for scalable data consumption
• Optimize workflows with Apache Airflow for efficient management
• Utilize Vector & Graph databases for robust data management at scale
• Hands-on projects for real-world experience in solving data challenges
• Create scalable systems & analyze performance for optimum results

Upskill to design, build & optimize data engineering pipelines that can handle complex, large-scale datasets. Prepare for demanding data roles by mastering advanced techniques with this comprehensive training.