15 Short Artificial Intelligence (AI) Courses on DeepLearning.AI

JavaScript RAG Web Apps with LlamaIndex
Dive into the world of constructing interactive, full-stack net functions that leverage the facility of Retrieval Augmented Era (RAG) capabilities. By means of this beginner-level course, you’ll be taught to assemble a RAG software in JavaScript, enabling clever brokers to discern and pull data from varied information sources to answer person queries successfully. With a deal with creating an enticing entrance finish that communicates seamlessly together with your information, this course is ideal for these with primary JavaScript abilities seeking to develop their net growth repertoire.

Efficiently Serving LLMs
This intermediate course gives a complete understanding of how one can deploy LLM functions effectively in a manufacturing atmosphere. Individuals will discover methods like KV caching to hurry up textual content era and delve into Low-Rank Adapters (LoRA) fundamentals and the LoRAX framework inference server. With a prerequisite of intermediate Python data, this course is designed for these seeking to scale their LLM functions successfully, catering to a big person base whereas balancing efficiency and pace.

Knowledge Graphs for RAG
Learners will get hands-on expertise constructing and using data graph programs to supercharge their retrieval augmented era functions. The course covers utilizing Neo4j’s Cypher question language and establishing data graph queries to offer LLMs with extra related context. Beneficial for these conversant in LangChain, this intermediate course bridges the hole between conventional databases and AI-driven question mechanisms.

Open Source Models with Hugging Face
Geared toward inexperienced persons, this course demystifies constructing AI functions with open-source fashions and instruments from Hugging Face. From filtering fashions primarily based on particular standards to writing minimal strains of code for varied duties, college students will discover ways to leverage the transformers library successfully. Moreover, the course covers how one can share and run AI functions simply utilizing Gradio and Hugging Face Areas, making it very best for these new to the AI discipline.

Prompt Engineering with Llama 2
Uncover the artwork of immediate engineering with Meta’s Llama 2 fashions. This beginner-friendly course teaches the perfect practices for prompting and deciding on amongst completely different Llama 2 fashions, together with Chat, Code, and Llama Guard. Individuals will discover how one can construct protected and accountable AI functions, emphasizing the sensible use of Llama 2 fashions in real-world situations.

Building Applications with Vector Databases
This beginner-level course is designed to show how one can develop functions powered by vector databases. Protecting six completely different functions, together with semantic search and picture similarity search, college students will be taught to implement these utilizing Pinecone. With primary data of Python, machine studying, and LLMs required, this course provides a sensible method to the thrilling prospects of vector databases.

LLMOps
This course introduces the perfect practices of LLMOps, from designing to automating the method of tuning an LLM for particular duties and deploying it. Individuals will be taught to adapt open-source pipelines for supervised fine-tuning, handle mannequin variations, and preprocess datasets. Geared toward inexperienced persons with primary Python data, this course is ideal for these seeking to delve into the operational elements of LLM deployment.

Automated Testing for LLMOps
This intermediate course focuses on growing automated testing frameworks for LLM functions and introduces steady integration (CI) pipelines. Individuals will learn the way LLM-based testing differs from conventional software program testing, implementing rules-based and model-graded evaluations. Fundamental Python data and expertise with LLM-based functions are conditions, making this course appropriate for builders seeking to improve their testing methods.

Build LLM Apps with LangChain.js
Increasing on utilizing LangChain.js, this intermediate course gives insights into constructing highly effective, context-aware functions. With a deal with orchestrating and chaining completely different modules, members will be taught important information preparation and presentation methods. Intermediate JavaScript data is required, making this course very best for builders aiming to reinforce their LLM software growth abilities.

Reinforcement Learning from Human Feedback
This intermediate course provides a mix of conceptual understanding and hands-on follow. It covers tuning and evaluating LLMs utilizing Reinforcement Studying from Human Suggestions (RLHF). Individuals will be taught to fine-tune the Llama 2 mannequin, assess efficiency, and perceive the datasets required for RLHF.

Building and Evaluating Advanced RAG Applications
Step into the superior area of RAG with this beginner-friendly course. It delves into enhancing retrieval methods and mastering analysis metrics to optimize RAG functions’ efficiency. Learners will discover sentence-window retrieval and auto-merging retrieval methods, specializing in evaluating the relevance and truthfulness of LLM responses via the RAG triad: Context Relevance, Groundedness, and Reply Relevance. Designed for these with a primary understanding of Python, this course equips you with the talents to develop sturdy RAG programs past the baseline iteratively.

Quality and Safety for LLM Applications
This course prioritizes the safety and integrity of LLM functions and is designed for inexperienced persons with primary Python data. Individuals will be taught to guage and improve the security of their LLM functions, specializing in monitoring safety measures and figuring out potential dangers comparable to hallucinations, jailbreaks, and information leaks. By exploring real-world situations, the course prepares you to safeguard your LLM functions in opposition to evolving threats and vulnerabilities, making certain a safe and dependable AI deployment.

Vector Databases: from Embeddings to Applications
This intermediate course unlocks the potential of vector databases for AI functions, bridging the hole between embeddings and sensible, real-world functions. Designed for these with primary Python data and an curiosity in information buildings, learners will develop environment friendly, industry-ready functions. The course covers a broad spectrum of functions, together with hybrid and multilingual searches, emphasizing utilizing vector databases to develop GenAI functions with out requiring intensive coaching or fine-tuning of LLMs. 

Functions, Tools, and Agents with LangChain
Delve into the most recent developments in LLM APIs and be taught to make use of LangChain Expression Language (LCEL) for quicker chain and agent composition. This intermediate course, appropriate for people with primary Python data and familiarity with LLM prompts, provides a hands-on method to using LLMs as developer instruments. By means of sensible workouts, learners will perceive how one can apply these capabilities to construct conversational brokers, enhancing their skill to create extra subtle and interactive AI functions.

Every course is designed with a selected talent degree, from newbie to intermediate, making certain learners can discover programs that match their present skills and assist them progress. Whether or not you’re seeking to construct safer LLM functions, create AI-powered net apps, or dive into vector databases, DeepLearning.AI’s quick programs present a complete studying path tailor-made to your wants. For these excited by advancing their AI abilities shortly and effectively, these programs provide a superb alternative to be taught cutting-edge AI applied sciences.

Good day, My identify is Adnan Hassan. I’m a consulting intern at Marktechpost and shortly to be a administration trainee at American Categorical. I’m presently pursuing a twin diploma on the Indian Institute of Expertise, Kharagpur. I’m enthusiastic about expertise and wish to create new merchandise that make a distinction.