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Claude Essentials for Developers, Accelerated
Duration
1 Day
Course
AICL-100B
Available Formats
Classroom Training, Online Training
Course Description
Overview
This Claude Essentials for Developers, Accelerated course is designed for experienced developers who already have working fluency with large language models and API-based AI development, and who need efficient, Claude-specific orientation rather than foundational LLM instruction. In a single hands-on day, participants build the Claude-specific mental model, make working API calls with reliable prompting patterns, and develop working capability with streaming, multi-turn conversations, tool use, and structured output. The course delivers the same end-state as the 2-day Essentials course but compresses the mental-model and first-integration material for an audience that does not need it spelled out.Objectives
Upon completion of the Claude Essentials for Developers course, students will be able to:
- Explain what Claude is, how large language models generate output, and what that mechanism means for reliability in software systems
- Authenticate to the Claude API and make working requests in Python or JavaScript
- Apply core prompting patterns — role framing, explicit criteria, and few-shot examples — to produce consistent, reliable outputs
- Implement streaming responses and handle partial output appropriately
- Use tool use to extract structured output that conforms to a defined schema
- Manage multi-turn conversations and context effectively within the model's context window
- Identify hallucination risks in their own code paths and design verification steps appropriate to the stakes
- Evaluate which development tasks are good candidates for Claude integration and which are not
Audience
Experienced software developers, backend and full-stack engineers, and technical professionals who already have hands-on experience with large language model APIs (OpenAI, Google, open-source models) and need focused, Claude-specific orientation without foundational LLM instruction
Prerequisites
-
Working proficiency in Python or JavaScript and experience consuming REST APIs. Prior hands-on experience building with at least one LLM API (calling, prompting, handling responses). Familiarity with JSON and basic software development practices.
Topics
- How Claude differs from other frontier LLMs developers have worked with — and why those differences matter for application design
- The Claude model family and selecting the right model for a task
- Claude-specific behaviors: steerability, refusals, and instruction-following characteristics
- Hallucination as a structural property and what that means for code design
- Authentication, request structure, and response handling
- Model selection and parameter tuning: temperature, max tokens, and stop sequences
- Error handling, rate limits, and production reliability basics
- Hands-on lab: build a working Claude API integration in your language of choice
- Role and system prompts: setting the frame for the model
- Explicit criteria versus vague instructions: why precision matters with Claude specifically
- Few-shot prompting: teaching format and behavior through examples
- Common prompting mistakes and how to diagnose them
- Implementing streaming responses and handling partial output
- Structuring multi-turn conversations in API calls
- The context window: what fits, what doesn't, and how to manage it
- When to start a new conversation versus extend an existing one
- What tool use is and how Claude decides when to call a tool
- Defining tools with JSON schemas for guaranteed output structure
- Reading tool calls and returning tool results correctly
- Hands-on lab: extract structured data from unstructured input using tool use
- Designing verification steps for AI-generated output in production code
- Identifying tasks that should be automated versus those that need a human in the loop
- Where Claude fits — and where it doesn't — in typical application architectures
- Next steps: deeper capabilities, production patterns, and certification paths
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- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
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title
Please take a moment to fill out this form. We will get back to you as soon as possible.
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