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Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya
High Demanding

Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya

Unleash innovation with Advance Generative AI and Agentic AI Training in Nairobi, Kenya by Techpratham—gain future-ready AI skills and lead the next tech revolution.

5/5(4,890 Reviews)

Level

Advanced

Duration

8 Weeks

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About Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya

Cultivate your career potential with Techpratham’s Advanced Generative AI and Agentic AI Training in Nairobi, Kenya—a high-impact program for ambitious ML engineers, developers, innovators, and founders driving East Africa’s digital growth.This industry-aligned curriculum goes beyond LLM fundamentals to help you build autonomous agents, orchestrate multi-agent systems, and deploy enterprise-grade AI solutions. Designed for Nairobi’s fast-growing sectors—FinTech, AgriTech, HealthTech, Logistics, E-commerce, and ClimateTech—you’ll work on real-world projects like AI-powered credit risk models, smart agricultural advisors, and intelligent supply chain systems.With expert mentorship, career guidance, and strong job-assurance, you’ll gain the skills and confidence to secure high-growth AI roles and lead innovation in one of Africa’s top tech hubs.

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Training Plan

01
About trainer

About trainer

Working professional who is carrying more then 10 years of industry experience.

02
Decks & Updated Content

Decks & Updated Content

Access to updated presentation decks shared during live training sessions.

03
e-Book

e-Book

E-book provided by TechPratham. All rights reserved.

04
Assignments & MCQs

Assignments & MCQs

Module-wise assignments and MCQs provided for practice.

05
Video Recording

Video Recording

Daily Session would be recorded and shared to the candidate.

06
Projects

Projects

Live projects will be provided for hands-on practice.

07
Resume Building

Resume Building

Expert-guided resume building with industry-focused content support.

08
Interview Preparation

Interview Preparation

Comprehensive interview preparation with real-time scenario practice.

Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya Course Curriculum

Python for AI & Automation (Foundation Layer)

Python for AI & Automation (Foundation Layer) builds core Python skills to automate tasks and create a strong base for AI and machine learning development.

Module 1: Python Essentials for AI
Python syntax, data types, control flow
Functions, modules, virtual environments
OOP concepts (important for agents)
Module 2: Python for Automation & AI
File handling, APIs, JSON
Web requests, REST API consumption
Async programming basics
Logging, exception handling
Module 3: AI-Ready Python Libraries
NumPy, Pandas
Requests, FastAPI (intro)
LangChain utilities (preview)

Introduction to Agentic AI & LLM Ecosystem

A foundational overview of how autonomous AI agents work with large language models to plan, reason, and execute tasks across modern AI systems.

What is Agentic AI?
Role of LangGraph, AutoGen, CrewAI in the ecosystem
OpenAI vs Azure OpenAI vs AWS Bedrock
Introduction to foundational concepts: Agents, Tasks, Graphs

 Basics of LangChain and LangGraph

An introductory overview of using LangChain and LangGraph to build, connect, and orchestrate intelligent, multi-step AI workflows.

LangChain recap: Chains, Tools, Memory
LangGraph architecture and why it matters
Installation, environment setup, and first LangGraph DAG

Exploring LangGraph Core Concepts 

A concise introduction to building stateful, multi-step AI workflows using LangGraph for agent orchestration and decision-making.

Nodes, Edges, State Machines
Understanding transitions and handlers
Building a simple agentic task flow

Python SDK and Node Configuration

An overview of setting up the Python SDK and configuring nodes to build, connect, and manage scalable AI workflows efficiently.

Deep dive into LangGraph Python SDK
Defining nodes and reactive transitions
Testing individual components with unit test strategy

Multi-Agent Setup with LangGraph

A practical introduction to designing and orchestrating multiple AI agents that collaborate and share state using LangGraph.

Multi-agent interaction via graph state
Introducing dynamic task allocation
Conditional logic and loops in graphs

Context Handling in Graphs

An overview of managing, passing, and maintaining context across nodes to enable consistent and intelligent decision-making in graph-based AI workflows.

Memory, buffers, and shared state
Prompt engineering for modular agents
Using LangChain tools inside LangGraph

Introduction to AutoGen

A beginner-friendly overview of AutoGen for building and coordinating conversational AI agents that collaborate to solve complex tasks.

AutoGen vs LangGraph
AutoGen architecture and agent design
Basic use-cases and sample projects

Building Custom Agents with AutoGen

A practical guide to designing, configuring, and deploying tailored AI agents using the AutoGen framework.

Defining roles and communication protocols
Tool integration in AutoGen
Building helper agents and supervisor agents

Combining AutoGen and LangGraph

 An introduction to integrating AutoGen agents with LangGraph to build scalable, coordinated, and state-aware multi-agent AI systems.

Orchestrating AutoGen inside LangGraph
Handling multi-turn conversations
Error handling and edge case design

Invoice Parsing with LangGraph

A practical overview of using LangGraph to extract, validate, and process invoice data through structured, multi-step AI workflows.

Designing agents for invoice interpretation
Simulating document variations

Image Processing Pipeline (OCR) 

An overview of building an OCR-based pipeline to extract, clean, and structure text from images for automated data processing.

Tools: Azure Cognitive Vision, AWS Textract, Tesseract
Building OCR extractor modules
Integration with LangGraph pipeline

Intermediate Graph Building

A focused overview of designing more complex graph-based AI workflows with conditional logic, state management, and optimized execution

Data validation agents
Retry and fallback agents
Visualizing graphs with tools like Graphviz

Case Study – Enterprise Invoice Agent

A real-world case study showcasing the design, deployment, and optimization of an AI-powered invoice processing agent for enterprise use.

Simulating multilingual invoices
Table extraction logic
Structured JSON/Excel output via agents

Agent Behavior Tuning

An overview of fine-tuning agent logic, prompts, and parameters to achieve more accurate, efficient, and predictable AI behavior.

Prompt templating with LangChain
Personality config for agents
Context vs history vs memory tradeoffs

Capstone Design Review

A comprehensive review of the final project, evaluating architecture, design decisions, and real-world readiness of the agentic AI solution.

Each participant/team presents their initial design
Review and feedback from mentors

Capstone Development Support 

Guided assistance and mentorship to help build, refine, and successfully complete a production-ready capstone project.

Debugging session
Review state transitions
Test cases writing session

Deployment of Capstone to Cloud 

An overview of deploying the final capstone project to a cloud platform with scalability, security, and production readiness

Pick Azure or AWS for deployment
Secure deployment best practices

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Additional Program Highlights

Learning Materials

Comprehensive study materials and resources

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Resume Writing

Professional resume building session

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Interview Preparation

Master your interview skills

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Live Project Demo

Real-world project demonstrations

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Who Should Take Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Job Roles For Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya

AI Agent Onboarding Manager

LLM Operations (LLMOps) Engineer

Synthetic Data Engineer

Key Projects

Advance Generative Ai and Agentic Ai Training in Nairobi, Kenya

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 AI-Powered Smart Customer Support Agent – Nairobi, Kenya

Our Advanced Generative AI and Agentic AI powered Smart Customer Support Agent enables Nairobi, Kenya businesses to automate real-time conversations across WhatsApp, web chat, and social platforms. The system understands context, resolves queries autonomously, escalates complex cases intelligently, and continuously learns from interactions, delivering 24/7 personalized multilingual support while reducing operational costs and improving customer satisfaction.


Key Highlights :-


  • Tools & Technologies Used: OpenAI GPT-4 / LLM APIs, LangChain, Pinecone (Vector Database),Twilio,WhatsApp Business API,React + Node.js
  • Real-time autonomous query resolution
  • Multilingual AI (English & Swahili support)
  • Self-learning knowledge base with RAG
  • Seamless CRM & ERP integrations

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AI Real-Time Financial Advisory Agent – Nairobi, Kenya

Designed for fintech startups and SACCOs in Nairobi, Kenya, this Agentic AI Financial Advisor analyzes real-time transaction data, market trends, and customer behavior to deliver personalized financial recommendations. It autonomously monitors risk, generates predictive insights, and interacts conversationally with users to provide budgeting guidance, fraud detection alerts, and investment suggestions through secure AI-driven interfaces.


Key Highlights :-


  • Tools & Technologies Used: Hugging Face Transformers,TensorFlow,Apache Kafka,FastAPI,PostgreSQL,Safaricom M-Pesa API
  • Real-time fraud detection & alerts
  • Autonomous financial planning agent
  • Predictive analytics for investment trends
  • Secure API integrations with fintech systems

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AI Smart Healthcare Monitoring & Diagnosis Agent – Nairobi, Kenya

This Generative AI and Agentic AI Healthcare Agent supports hospitals and clinics in Nairobi, Kenya with real-time patient monitoring, symptom analysis, and automated medical documentation. It assists doctors by generating preliminary diagnostic suggestions, tracking patient vitals via IoT devices, and autonomously scheduling follow-ups while ensuring data privacy compliance and improving healthcare service efficiency.


Key Highlights :-


  • Tools & Technologies Used: Google Cloud Vertex AI,PyTorch,Docker,Kubernetes,MongoDB,FHIR APIs
  • AI-assisted real-time diagnosis support
  • Automated EMR documentation generation
  • IoT-based patient health monitoring
  • HIPAA-aligned secure data handling

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Our Success Mantra

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Commitment

  • Ensuring quality training every day

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Fulfillment

  • Meeting learning goals with confidence

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Accomplishment

  • Students achieving industry-ready expertise

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Beyond Courses:

Additional Support We Provide

24/7 Support

LinkedIn Profile

Resume Writing

Alumni Sessions

Interview Preparation

Live Projects

As a candidate from Kenya, how can this Advanced Generative AI and Agentic AI training improve my career prospects?

Is this course in line with Kenya's expanding fintech and telecommunications industries?

What kind of certification will I receive upon finishing the program?

How does Techpratham assist with career growth after completing the course?

Can this training help me launch an AI-focused business in Kenya?

Does this course cover AI ethics and responsible AI practices relevant to Kenya?

Your client is a Kenyan financial institution handling 15M+ documents across English and Swahili. They need a secure RAG-based internal knowledge assistant. How would you design ingestion, chunking, embedding, indexing, retrieval optimization, and hallucination control under regulatory constraints?

A telecom enterprise in Nairobi wants a chatbot trained on internal SOPs. Would you fine-tune an LLM or implement RAG? Justify with cost, latency, maintainability, and governance implications.

Design a multi-agent system where agents handle document verification, fraud detection, credit scoring explanation, and customer communication. How would you coordinate them?

If your deployed legal advisory AI starts generating fabricated case references, how would you diagnose and mitigate the issue in production?

How would you evaluate embedding performance for Swahili-heavy enterprise search systems?

An AI assistant receives 200K daily queries. How do you optimize inference cost without sacrificing quality?

Industry-Recognized Certification

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News Highlights

TechPratham Introduces Hire-Train-Deploy Model to Transform HR & ERP Talent in the AI Era
TechPratham Empowering Future Professionals Through AI-Focused HR & ERP Training

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TechPratham's Hire-Train-Deploy Approach Reshaping HR & ERP Careers in the AI-Driven Industry
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