Introduction Imagine asking your AI assistant a question, and instead of getting a quick and thoughtful response, you end up waiting—and waiting—until finally, an answer appears that’s not quite what you hoped for. Frustrating, right? This happens because many AI … Read More
Gain In-Demand AI Skills. Transform Your Career
Future-Proof Your Career with Our AI Bootcamp.
Experience the future of Computer Vision & Machine Learning!
Explore cutting-edge advancements and practical solutions in our interactive workshop. Discover how to leverage open-source models, tackle industry challenges, and deploy ML models effectively in production. Join us for #ComputerVision2024 and gain valuable insights into this transformative technology.
This workshop is perfect for:
Computer Engineers, Software Engineers, and aspiring ML Engineers seeking hands-on experience and industry best practices.
Master LLMs in Our Hands-On Studio Workshop
Build the Future of AI-Powered Applications with Large Language Models.
What You’ll Learn:
LLM Fundamentals: Gain a deep understanding of LLM architecture, capabilities, limitations, and ethical considerations for responsible development.
Prompt Engineering: Master the art of crafting effective prompts to extract specific information, generate creative content, and guide LLM behavior for desired outputs.
Fine-tuning & Customization: Learn how to fine-tune pre-trained LLMs on your own data to create specialized models for specific tasks and domains.
Building LLM-Powered Applications: Develop real-world applications such as chatbots, question-answering systems, text summarizers, code generators, and more.
Deploying Your LLMs: Explore deployment options for making your LLM-powered applications accessible to users, from APIs to web interfaces.
Who Should Attend:
Developers and engineers looking to build LLM-powered applications.
Data scientists and AI practitioners seeking to expand their skillset into NLP and LLMs.
Product managers, marketers, and anyone interested in exploring the transformative potential of LLMs for their industry.
Workshop Highlights:
Hands-On Studio Environment: Learn by doing! We provide all the tools, datasets, and resources needed to experiment with LLMs and build your own applications.
Expert Guidance: Our instructors are experienced LLM practitioners who will share practical insights, best practices, and real-world case studies.
Collaborative Learning: Connect with a community of like-minded peers, exchange ideas, and collaborate on exciting projects.
Duration: 1 Week
Day 1: Introduction to LLM and RAG Frameworks
Morning Session:
•Overview of Large Language Models (LLMs)
•Introduction to Retrieval-Augmented Generation (RAG)
•Use cases and benefits in enterprise settings
Afternoon Session:
•Deep dive into the LLM RAG Roadmap
•Tools and frameworks for LLM and RAG development
Day 2: Setting Up the Environment
Morning Session:
•Setting up the development environment (Python, Jupyter, relevant libraries)
•Accessing and preparing company-specific data (structured and unstructured)
Afternoon Session:
•Data preprocessing and cleaning techniques
•Introduction to chunking strategies for RAG Evaluation of LLM RAG Chunking Strategy
Day 3: Building the RAG Application
Morning Session:
•Developing the retrieval component: indexing and searching company data
•Implementing the augmented generation component: integrating LLM with retrieval results
Afternoon Session:
•Hands-on lab: Building a basic RAG application
•Testing and validating the application with sample queries.
Day 4: Fine-Tuning NER Models for PII Detection
Morning Session:
•Introduction to Named Entity Recognition (NER)
•Techniques for fine-tuning NER models for PII detection
Afternoon Session:
•Implementing PII filtration in the RAG framework
•Hands-on lab: Fine-tuning an NER model with company data
Day 5: Verification and Validation Methods
Morning Session:
•Developing verification methods for LLM response accuracy
•Quantitative metrics for evaluating LLM and RAG performance
Afternoon Session:
•Implementing and testing accuracy quantification methods
•Hands-on lab: Applying verification techniques to the RAG application
Day 6: Integration and Deployment
Morning Session:
•Integrating the RAG application with enterprise systems
•Deployment strategies for scalable and secure applications
Workshop 1: For Fresh ML/CV/NLP Engineers
Accelerating Your ML Career: Mastering Advanced Concepts and Industry Best Practices
Course Outline:
Day 1: Foundations Review and Modern CV Deep Dive
- Fundamentals Refresh: Brief review of core ML concepts (supervised/unsupervised learning, model evaluation, etc.) to ensure everyone’s on the same page.
- Advanced CV Architectures: Deep dive into cutting-edge architectures like Transformers, Vision Transformers (ViT), and their applications in object detection, image segmentation, etc.
- Transfer Learning and Fine-Tuning: Hands-on exercises fine-tuning pre-trained models on custom datasets.
Day 2: The ML Engineering Toolkit
- Model Optimization: Techniques for model compression, quantization, and knowledge distillation to improve efficiency.
- MLOps: Introduction to the principles and tools of MLOps for robust model deployment and monitoring.
- Cloud ML Platforms: Overview of cloud-based ML services like AWS SageMaker, Google Vertex AI, etc., and how to leverage them for scalable model training and deployment.
Day 3: Industry Best Practices and Career Development
- Real-World Projects: Case studies of successful CV applications in various industries (healthcare, autonomous vehicles, etc.).
- Ethical Considerations: Discussion of bias, fairness, and transparency in ML models.
- Building Your ML Portfolio: Guidance on showcasing your skills, networking, and job searching in the ML field.
Workshop 2: For Advanced/Senior ML/NLP/CV Engineers
Pushing the Boundaries: Cutting-Edge Research and Applications in CV and LLM
Course Outline:
Day 1: Recent Advances in CV
- Foundation Models: Deep exploration of large-scale models like CLIP, DALL-E, and their impact on CV research.
- Multimodal Learning: Combining vision and language for tasks like image captioning, visual question answering, etc.
- Self-Supervised Learning in CV: Latest techniques for learning from unlabeled data.
Day 2: The LLM Revolution
- Transformer Architectures: Understanding the inner workings of Transformers and their variations (BERT, GPT, etc.).
- Prompt Engineering: Techniques for eliciting desired outputs from LLMs.
- Applications of LLMs: Case studies of using LLMs in natural language understanding, code generation, and creative content generation.
Day 3: The Future of CV and LLM
- Research Frontiers: Exploring emerging trends like embodied AI, neuro-symbolic AI, and continual learning.
- Ethical Implications: Deepening the discussion of the potential societal impacts of advanced AI.
- Panel Discussion/Q&A: Interactive session with experts to discuss the future landscape of the field.
Workshop 3: For Executive-Level Audiences
AI Demystified: The Executive's Guide to Understanding and Leveraging Machine Learning
Course Outline:
Day 1: ML Fundamentals for Decision Makers
- What is ML? A non-technical overview of ML concepts and terminology.
- The Business Value of ML: How ML is transforming industries and creating new opportunities.
- Key Use Cases: Examples of successful ML applications in marketing, finance, healthcare, and other domains.
Day 2: Building an AI Strategy
- Identifying ML Opportunities: How to assess where ML can add value to your organization.
- Data Strategy: The importance of high-quality data and how to build a data infrastructure.
Talent Acquisition and Development: Building an effective ML team. - Ethical and Responsible AI: Considerations for ensuring your AI initiatives are aligned with your company’s values.
Day 3: The Future of AI and Its Implications
- Emerging Trends: An overview of the latest developments in AI research and technology.
- The Impact of AI on Society: Discussion of the potential benefits and risks of AI.
- Preparing for the AI-Powered Future: Strategies for staying ahead of the curve.
Additional Notes:
Hands-on Labs: Incorporate interactive labs where participants can experiment with models and tools.
Networking Opportunities: Facilitate networking sessions to allow participants to connect and collaborate.
FAQs
We offer beginner, intermediate, and advanced level training programs to cater to diverse skill levels.
We provide both online and in-person training options, with flexible scheduling to accommodate your team’s needs.
Yes, we can tailor our training content and delivery methods to address the specific AI challenges and opportunities within your industry.
Let’s build something different
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