Announcing Gen AI 360: Activeloop Collaborates with Towards AI to Launch Free Skill Certification Courses on AI Search, LangChain, LlamaIndex, Vector Databases, & Foundation Models
Mountain View, CA. June 20 2023 - Activeloop is proud to announce the launch of industry-pioneering educational certifications on Large Language Models, Deep Lake, the vector database for all AI data, and LangChain, a framework for developing applications powered by language models. The certification program, available at no cost, is designed as part of the Gen AI 360: Foundational Model Certification program in collaboration with Intel and Towards AI.
Here are the four courses currently available to everyone free of charge:
LangChain & Vector Databases for Production.
Combines a comprehensive overview of foundation model theory and practical projects with LangChain and Deep Lake, equipping AI developers with the tools they need to apply Large Language Models across industries.Train & Fine-Tune Models for Production.
Covers various aspects of working with LLMs. The course provides an in-depth understanding of LLMs, their evolution, architectures like Transformers and GPT, and techniques for training, fine-tuning, and improving their performance. The course delves into topics such as data preparation, LLMOps, benchmarking, domain-specific LLMs, and advanced methods like Reinforcement Learning from Human Feedback (RLHF). It includes practical projects and hands-on examples, allowing learners to gain experience in fine-tuning LLMs using techniques like LoRA, SFT, and RLHF, as well as training custom models with tools like Cohere and Deep Lake. Overall, the course aims to equip learners with the knowledge and skills necessary to effectively work with LLMs in production environments.Retrieval Augmented Generation for Production with LangChain & LlamaIndex.
This is a comprehensive course on Retrieval Augmented Generation (RAG) using LlamaIndex and LangChain, covering both theoretical concepts and practical applications. It provides an in-depth understanding of RAG techniques, including advanced methods like Deep Memory for improved retrieval accuracy. The course offers hands-on projects across various industries, such as legal, financial, and biomedical, enabling learners to build production-ready RAG solutions. Additionally, it covers topics like RAG agents, evaluation metrics, and observability, equipping learners with the skills to develop and deploy AI assistants and multi-modal applications effectively.Building AI Search: Multi-Modal RAG, PaperQA2, RAFT, & GraphRAG for Production.
Build multi-modal AI Search and Deep Reasoning using state-of-the-art techniques and open-source models like ColBERT, ColPali, and Meta Llama.
“Reaching over 400,000 AI developers monthly, we’re passionate about educating and upskilling engineers in this rapidly growing field. That is why we designed a practical course engineers can take to implement AI into their company processes or use Foundational Models to build entirely new products,” said Louie Peters, CEO of Towards AI.
“Every company will be adding Foundational Models and vector databases to their day-to- day operations and the products they build very soon. Upon course completion, Deep Lake Certified developers can harness the full potential of Large Language Models and advanced AI technologies like Deep Lake and LangChain. Companies that want to achieve a competitive advantage should include these frameworks in their toolset. We’re already seeing solutions powered by LangChain and Deep Lake rapidly gaining adoption,” said Davit Buniatyan, CEO of Activeloop.
“I believe engineers and technology executives could greatly benefit from taking this course to stay at the forefront of AI,” said Arijit Bandyopadhyay, CTO – Enterprise Analytics & AI, Head of Strategy – Cloud & Enterprise, DCAI Group at Intel Corporation. “Intel continues to be at the vanguard of AI and new technology adoption. This Foundation Model Certification could help better equip the next generation of innovators with what they need to succeed with Generative AI and Large Language Models. It could also contribute to the broader adoption of AI applications and solutions across various industries.”
Activeloop’s Deep Lake is designed to combine the best of both data lakes and vector databases, enabling companies to build their own data flywheels to fine-tune their Large Language Models on complex data beyond embeddings - such as text, image, video, or audio, and power AI products. LangChain, in its turn, seamlessly connects Deep Lake datasets with Foundational Models in diverse use cases - from understanding GitHub repositories to analyzing financial statements.
“We created this course with great support from industry leaders, like Intel and AWS, as well as key innovative players on the market,” said Mikayel Harutyunyan, Activeloop Head of Marketing and the creator of the certification. “Our hope the certification will foster the adoption of cutting-edge AI technology within any engineering organization across industries.”
To learn more about the Deep Lake Foundation Model Certification and to sign up for free, visit Gen AI 360 Certification page.
About Activeloop
Activeloop is building Deep Lake, a vector database for all AI data. With Deep Lake, ML teams can store and manage complex data, such as embeddings, text, images, audio, videos, annotations, or tabular data, in a deep learning-native format and stream them to ML frameworks in real time. Matterport, Bayer Radiology, Flagship Pioneering, & others use Deep Lake.
About Towards AI
Towards AI simplifies AI learning & AI product building with 30-50 weekly blogs & tutorials for 400K followers and their 60K-member Discord community. Towards AI addresses AI students’ and practitioners’ challenges through community-driven practical courses and a Jobs board.