Function-calling and data extraction with LLMs
By DeepLearning.AI · June 19, 2026
Course Overview
This intermediate‑level DeepLearning.AI course teaches how to harness large language models for function calling and data extraction. In just one hour, learners gain actionable skills to automate workflows and integrate LLMs via APIs, a capability increasingly demanded in 2026.
Overall Rating: 4.5/5 | Best For: Mid‑level AI engineers seeking LLM function‑calling skills | Access: Free | Ease of Use: 4.7/5
What Is This Course?
This intermediate‑level DeepLearning.AI course teaches how to harness large language models for function calling and data extraction. In just one hour, learners gain actionable skills to automate workflows and integrate LLMs via APIs, a capability increasingly demanded in 2026.
Who This Course Is For
AI engineers — Looking to add function‑calling capabilities to existing models.
Data engineers — Want to automate data extraction pipelines with LLMs.
Product managers — Seeking to prototype AI‑driven features quickly.
ML researchers — Interested in the latest LLM integration patterns.
What You Will Learn
Fundamentals of Function Calling
Covers the theory behind LLM‑driven function calls, including prompt patterns and response handling. Learners understand when to use this technique versus traditional APIs.
Designing Robust Prompts
Teaches prompt engineering strategies that produce reliable function‑call outputs, reducing hallucinations and improving data quality.
API Integration Basics
Walks through connecting LLM responses to external APIs, enabling real‑time data retrieval and action execution.
Error Handling & Validation
Shows how to validate function‑call arguments and gracefully handle failures, essential for production reliability.
Security & Privacy Considerations
Explores best practices for protecting sensitive data when LLMs invoke external services.
Deploying at Scale
Guides on scaling function‑calling pipelines using cloud services, monitoring, and cost‑optimization tactics.
How to Access This Course
The course is 100% free, requires no credit card, and is fully self‑paced on the DeepLearning.AI platform. Learners can start immediately and access all materials without charge.
Where This Course Excels
Practical, hands‑on examples — Each module includes live code snippets that can be copied into production.
Focused on real‑world automation — Directly applicable to building AI‑augmented workflows.
Free and self‑paced — No enrollment fee or credit‑card requirement.
Limitations & What It Doesn't Cover
Limited depth on advanced scaling — Enterprise‑level scaling strategies are only introduced briefly.
Assumes prior LLM knowledge — Complete beginners may need a prerequisite prompt‑engineering course.
Getting Started
- Step 1: Visit deeplearning.ai and navigate to the Courses section.
- Step 2: Locate "Function-calling and Data Extraction with LLMs".
- Step 3: Click "Enroll Free" to add the course to your dashboard.
- Step 4: Open Module 1 and begin the hands‑on lessons.
Is This Course Worth It?
For professionals who already understand basic prompting, this free hour‑long course delivers high ROI by teaching concrete function‑calling techniques that can be deployed immediately. Its strongest value is the practical integration guidance; the main limitation is the brief coverage of large‑scale production concerns. Overall, it’s a worthwhile investment for anyone aiming to automate data workflows with LLMs.
Alternatives to Consider
Intro to Prompt Engineering (Coursera) — Covers foundational prompting before moving to function calls
AI Automation with LangChain (edX) — Focuses on building end‑to‑end pipelines using LangChain
OpenAI Function Calling Quickstart (OpenAI Docs) — Provides concise, official guidance directly from the model provider
Verdict
Bottom Line: If you need a fast, practical path to adding LLM function‑calling to your toolkit, this free DeepLearning.AI course is a solid choice. It equips you with deployable skills without financial commitment, though larger enterprises may require deeper scaling resources.
Key Takeaways
- Learn to design prompts that reliably trigger function calls.
- Integrate LLM outputs with external APIs for real‑time data.
- Apply security best practices when handling sensitive information.
- Scale simple pipelines using cloud‑native tools.
Frequently Asked Questions
AI Tools to Use Alongside This Course
Practising what you learn is where the real value kicks in. These tools pair directly with the skills covered in this course:
LangChain
Provides a framework to build and manage LLM function‑calling workflows taught in the course
Ready to put your new skills to work?
Browse All AI Tools →Last Reviewed: June 2026 | Reviewed by theaitoolsbox.com editorial team
🎯 Who This Course Is For
AI engineers Looking to add function‑calling capabilities to existing models. Data engineers Want to automate data extraction pipelines with LLMs. Product managers Seeking to prototype AI‑driven features quickly. ML researchers Interested in the latest LLM integration patterns.
Pros & Cons
What We Love
- Practical, hands‑on examples: Each module includes live code snippets that can be copied into production.
- Focused on real‑world automation: Directly applicable to building AI‑augmented workflows.
- Free and self‑paced: No enrollment fee or credit‑card requirement.
Watch Out For
- Limited depth on advanced scaling
- Assumes prior LLM knowledge
Course Details
- Price
- Free
- Level
- Intermediate
- Duration
- 1 hour
- Topic
- Task Automation
- Instructor
- DeepLearning.AI
- Rating
- ★ 4.5/5
- Platform
- DeepLearning.AI
More Free AI Courses
Orchestrating Workflows for GenAI Applications
Task AutomationDeepLearning.AI’s one‑hour intermediate course teaches professionals how to design and manage end‑to‑end GenAI pipelines. It focuses on practical orchestration techniques …
Fast & Efficient LLM Inference with vLLM
LLM ServingThe Fast & Efficient LLM Inference with vLLM course equips intermediate AI engineers with practical techniques to serve large language …
Building Multimodal Data Pipelines
Data ProcessingDeepLearning.AI's Building Multimodal Data Pipelines course equips data engineers and ML practitioners with a practical framework for integrating text, image, …
Agent Skills with Anthropic
AgentsThis one‑hour intermediate course from DeepLearning.AI equips product teams and AI practitioners with practical techniques for prompting, fine‑tuning, and integrating …
Build and Train an LLM with JAX
Deep LearningDeepLearning.AI’s one‑hour, intermediate‑level course teaches engineers how to build and fine‑tune large language models with JAX. It focuses on practical …
TensorFlow Developer Professional Certificate
Deep LearningThe TensorFlow Developer Professional Certificate from DeepLearning.AI offers a structured pathway for professionals aiming to build production‑ready machine‑learning models. As …