Sep 9th – December 21st

Build with AI:
Python and AI Agent Development

VENUE: Aardvark Jerusalem Office (Ezrat Israel 3)

Goals

Build practical Python programming skills from the ground up, no prior experience required.
Understand how modern AI and Large Language Models (LLMs) work, and learn to communicate with them via API.
Design, build, and deploy AI agents capable of using tools, memory, and external data sources.
Gain real exposure to the Israeli tech industry through TechTrek tours and workshops with industry leaders.
Complete an AI agent capstone project to present to employers and universities.

Methodology

A semester of immersive training in Python programming and AI agent development, using the TaskForce technique – a learning method based on projects and tasks, inspired by the internationally acclaimed 42 School organization. Participants learn by building, collaborating, and teaching each other, developing both the technical skills and the problem-solving mindset needed to thrive in the modern tech industry. After completing the program, talented participants will have the opportunity to intern at high-tech companies, gaining hands-on professional experience alongside seasoned developers.

Tech Trek

During the tours, we offer educational workshops on topics such as entrepreneurship, software development, AI product development, and more – providing important insights into the world of high-
tech startups and AI companies. Our tours are multidimensional: we aim to expose you to employees at different levels, from senior management to the production floor, so you can understand how Israel’s leading technology companies are built and operated.

Program

Week	Duration	Topic	Activity
1	15 academic hours	Intro to Programming & AI Tools	What is programming and why does it matter? Overview of the modern tech landscape and artificial intelligence. Setting up the environment: VS Code, terminal basics, GitHub account. Introduction to AI-powered coding assistants (GitHub Copilot, Claude). First Python lines: print, variables, and simple logic.
2	15 academic hours	Python Fundamentals - Part 1	Data types: strings, numbers, booleans, lists, and dictionaries. Control flow: if/else, loops (for, while). Writing students' first functions. Hands-on project: Build a simple text-based guessing game.
3	15 academic hours	Python Fundamentals - Part 2	Functions, scope, and modules. Working with files: reading and writing. Error handling with try/except. Introduction to libraries: os, random, datetime. Mini-project: CLI application for personal task management.
4	15 academic hours	APIs & Working with External Data	What is an API? HTTP requests and REST basics using the requests library. Parsing JSON responses. Authentication: API keys and tokens. Hands-on: Connect to a real public API (weather, news, etc.) and display results. TechTrek tour.
5	10 academic hours	Introduction to AI & Large Language Models	What are LLMs and how do they work? (Conceptual overview). Key concepts: tokens, prompts, context windows, temperature. Overview of major AI providers: OpenAI, Anthropic, Google. Making a first API call to an LLM. Prompt engineering basics: zero-shot, few-shot, chainof-thought. TechTrek tour.
6	15 academic hours	Building with OpenAI & Anthropic APIs	Deep dive into the Chat Completions API. System prompts and role-based messages. Streaming responses for improved user experience. Managing conversation history and context. Hands-on project: Build a simple AI chatbot in Python.
7	15 academic hours	AI Agent Fundamentals	What is an AI agent? Agents vs. chatbots vs. pipelines. The ReAct pattern: Reasoning + Action. Introduction to tools and function calling. Building a basic agent loop from scratch. TechTrek tour.
8	15 academic hours	Tools, Function Calling & Agent Loops	Defining and registering tools (functions) for LLMs. How models decide when and how to invoke tools. Building multi-turn agents with tool usage. Practical tools: web search, calculator, file reader. Project: Build an agent that answers questions using real-time data.
9	15 academic hours	Agent Frameworks - LangChain & LlamaIndex	Introduction to agent frameworks and why they exist. LangChain: chains, agents, and memory. LlamaIndex: document indexing and retrieval. Choosing the right tool for the job. Hands-on: Refactor your agent using LangChain.
10	15 academic hours	Retrieval Augmented Generation (RAG)	Why RAG? The problem of LLM knowledge limitations. Vector databases: what they are and how they work (ChromaDB, Pinecone). Embeddings: converting text to numbers. Building a RAG pipeline: ingestion – embedding – retrieval - generation. Project: Build a Q&A bot on custom personal documents. TechTrek tour
11	15 academic hours	Memory, State & MultiStep Agents	Types of memory in AI agents: in-context, external, episodic. Implementing persistent memory for agents. Planning and decomposing multi-step tasks. Introduction to multi-agent systems. Hands-on: Build an agent that remembers user preferences across sessions.
12	15 academic hours	Web Interfaces for AI Agents	Introduction to web development for AI: Flask basics. Creating REST API endpoints that serve AI capabilities. Connecting the agent backend to a simple frontend. Deployment basics: environment variables, secret management. Introduction to Streamlit for rapid AI app prototyping. TechTrek tour.
13	15 academic hours	Capstone Project - Part 1: Planning & Architecture	Teams form and propose AI agent project ideas: Define the problem, target user, and use case. Design agent architecture: tools, memory, data sources. Set up project repository and development environment. Sprint planning and task breakdown.
14	20 academic hours	Capstone Project - Part 2: Development	Full development sprint: implement core agent logic, tool integrations, and data pipeline. • Peer code reviews and debugging sessions. Instructor check-ins and feedback. Focus on reliability: error handling, edge cases, and fallback behavior. TechTrek tour.
15	10 academic hours	Capstone Project - Part 3: Polish & Deploy	Connect the agent to a user interface (Streamlit or Flask). Deploy to a cloud environment (Render, Railway, or HuggingFace Spaces). Write project documentation and README. Security review: API key management, rate limiting, input validation. Final testing and quality assurance.
16	20 academic hours	Demo Day & Course WrapUp	Capstone project presentations and live demos. Guest judges from the Israeli tech industry. Peer feedback and reflection. AI career paths: roles, skills, and next steps. Course evaluation, certificates, and celebration.

A Methodian lead Program

Methodian, a leading provider of training and placement services in the high-tech industry.
Methodian has developed a proven methodology to help aspiring developers acquire the skills and hands-on experience they need to succeed in today’s competitive job market.

The program begins with a dynamic semester of learning how to build with AI using Python and AI agent development. Through the TaskForce method — a hands-on, project-based learning model inspired by the internationally acclaimed 42 approach — participants gain real-world experience creating AI-powered tools, automations, and intelligent applications.

After the training semester, the participants will have the opportunity to intern in high-tech or start up companies for a semester. This internship program is designed to help participants improve their skills and gain practical experience by working alongside experienced industry professionals. Participants will be exposed to different companies and industry sectors, providing them with valuable insights into the latest trends and technologies.

Overall, the program aims to provide participants with quality meetings and exposure to various sectors of the software world, helping them build their knowledge, skills and professional network.

Build with AI: Python and AI Agent Development