Top rated in Kenya: 4.9/5 rating from 80+ Google reviews

Applied AI Engineering Course: Build and deploy production AI agent systems

Learn to design, evaluate, and deploy AI agents using LangChain, LangGraph, and Langfuse, covering everything from your first tool-calling agent to production-grade RAG, fine-tuning, and multi-agent orchestration. Course curriculum is anchored on the Databricks Certified Generative AI Engineer Associate certification.

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Overview

Become an AI Engineer, Agentic AI Engineer, or AI Systems Engineer

Our immersive core program is built to bridge the gap between learning and employment. We combine personalised mentorship – smaller classes equals better support & greater outcomes; project-based learning – build real-world projects; and job placement support to ensure you don’t just graduate, you launch a career.

AI Engineering is where the generative AI boom actually gets built. Every company deploying LLMs in production needs engineers who can move past demos, chatbots that work in a sandbox but break under real traffic, bad input, or cost pressure, and build systems that hold up: agents with proper guardrails, retrieval pipelines that don’t hallucinate, evaluation frameworks that catch regressions before users do. That gap between ‘I can call an API’ and ‘I can ship a production AI system’ is exactly where demand, and pay, is concentrated right now.

Career Stage

Kenya Salary Range

Global Remote Range

Entry-Level

KES 70K – 140K monthly

$115K – 170K annually

Mid-Level

KES 180K – 280K monthly

$150K – 240K annually

Senior/Expert

KES 350K+ monthly

$220K – 310K+ annually

In the first phase, you’ll build your first working AI agent using the LangChain and LangGraph ecosystem, learning to control it with structured prompting, tool calling, and MCP integrations. From there you move into agent loops and multi-agent orchestration, then into advanced context engineering: production-grade RAG with hybrid search and re-ranking, memory systems that persist across sessions, and fine-tuning workflows using LoRA on open-weight models, so you know exactly when weight-level adaptation is worth it and when it isn’t.

In the second phase, you shift from building agents to running them like production software. You’ll instrument systems for full observability with LangSmith and Langfuse, build evaluation pipelines and LLM-as-judge frameworks that gate releases instead of relying on gut feel, defend against prompt injection and data leakage, and deploy and cost-optimize agents for real-world serving constraints.

This course is best suited for professionals who want to build production-grade agentic systems for companies. The course steps beyond typical AI usage, build with AI, or even no-code AI agents into actual engineering of generative AI systems. Hence, this course is best suited for:

  • Software Developers: You already know how to build and ship code. Skip the bridge modules entirely and go straight into the AI engineering core, agents, RAG, evaluation, and production deployment, building on backend skills you already have.
  • Data Analysts and Data Scientists: You know how to work with data and models but haven’t built backend systems. Start with our FastAPI Backend Development bridge to get the engineering foundation you need, then move into the same AI engineering core.
  • Career Switchers and Beginners: New to programming entirely. Start from Python Programming fundamentals, build up through backend development, and land in the same AI engineering core as everyone else, no prior coding background required.

Choose the learning schedule that best works for you

For hybrid options, in-person classes are at our Westlands/Lavington offices. If outside Nairobi, try our fully remote options:

Full-Time Hybrid

Ideal for learners WITHOUT full-time work or school commitments

  • Graduate in 5 months
  • 35-hour weekly commitment
  • 3 in-person and 2 online classes weekly – Most popular
  • Classes run from 9am – 2pm with daily take-home projects
  • Cohort intakes every 2 months
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Part-Time Flexible

Both hybrid or remote, ideal for learners with full-time commitments

  • Graduate in 8 months
  • 20-hour weekly commitment
  • Online evening classes on weekdays – Most flexible
  • In-person/online classes on Saturdays from 10am – 2pm
  • Cohort intakes every 2 months
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Full-Time Remote

Ideal for learners available full-time but outside Nairobi & its environs

  • Graduate in 5 months
  • 35-hour weekly commitment
  • All classes are online every weekday – New option in 2026
  • Classes run from 9am – 2pm with daily take-home projects
  • Cohort intakes every 4 months
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CURRICULUM

What you’ll learn in our Applied AI Engineering course

We offer the most advanced AI engineering curriculum in the local market, covering multi-agent orchestration and production-grade evaluation most bootcamps skip entirely, so you graduate able to ship systems, not just demo them.

Learn the fundamentals of programming with Python. By the end of the module, you should have an apt understanding of building scripts with Python, interacting with databases, and sourcing data through APIs and scraping.

  • Dev Foundations: Git version control, Linux, and CLI/Terminal foundations
  • Python Basics: variables, conditional statements, loops, and functions
  • Data Types: strings, lists, files, tuples, sets, and dictionaries
  • Using Web Services: regular expressions, web scraping, and APIs
  • Advanced Python: object-oriented programming, unit-testing, and working with databases

By the end of this module, you’ll be able to design and build REST APIs, validate data with Pydantic, write and reason about async Python, work with databases from your API layer, and containerize and deploy a service with Docker, the exact foundation you need before building and deploying AI agents in the core curriculum.

  • API Fundamentals: HTTP methods, REST principles, and designing endpoints that make sense
  • FastAPI & Pydantic: Building typed, validated APIs with FastAPI routing and Pydantic data models, the same validation approach you’ll use for structured AI outputs later
  • Async Python: Writing and reasoning about async/await code, the backbone of how agents call tools and APIs concurrently
  • Databases & Persistence: Connecting your API to a database, working with an ORM, managing schema and migrations
  • Testing & Auth: Writing tests for your API, handling authentication and API keys
  • Docker & Deployment: Containerizing and deploying your service

Learn to build, control, and orchestrate AI agents using the LangChain and LangGraph ecosystem. By the end of this module, you’ll go from your first working agent to coordinating multiple agents working together on a task.

  • Foundations of Agentic AI: Understand transformer architecture at an engineer’s level, learn model economics and selection, and build and trace your first agent with LangChain and LangSmith
  • Prompting & Tool-Calling: Write reliable, structured prompts with Pydantic schemas, design and register tools your agent can call correctly, connect to external MCP servers, and build an evaluation set to measure whether a change actually helped
  • Agent Loops with LangGraph: Model agents as explicit state machines with proper stopping criteria, persist and resume runs across failures, and learn when a task needs a single agent versus sub-agents with isolated context
  • Multi-Agent Orchestration: Choose the right coordination pattern for a given problem, hand-off, supervisor, or decentralized, implement delegation and parallel fan-out, and understand the A2A protocol along with where multi-agent systems break down

Move beyond a working prototype into production-quality context and adaptation. By the end of this module, you’ll build retrieval systems that actually work, give your agents persistent memory, and know exactly when fine-tuning is worth the cost.

  • Retrieval-Augmented Generation (RAG): Build a full vector retrieval pipeline, then take it to production quality with hybrid search, re-ranking, query transformation, multi-modal retrieval, and graph-based RAG, measuring every optimization against a real baseline instead of eyeballing results
  • Memory: Distinguish memory from retrieval, manage conversation state under context pressure, and implement long-term cross-session recall with explicit policies for what an agent remembers, and deliberately forgets
  • Fine-Tuning: Diagnose whether a quality gap needs better prompting, better retrieval, or fine-tuning, then curate a dataset and run a real LoRA fine-tune on an open-weight model, proving the result beats both the base model and a prompted baseline

Shift from building agents to running them like production software. By the end of this module, you’ll have full observability into your systems, evaluation pipelines that gate releases, defenses against real-world attacks, and a deployed, cost-optimized agent.

  • Tracing & Evaluation (LangSmith): Instrument every step of your agent for observability, build eval sets with real ground truth, and construct an LLM-as-judge while accounting for its known biases
  • Advanced Evaluation & Monitoring (Langfuse): Calibrate judges against hand-labeled data, catch regressions across prompt, model, and RAG changes before they ship, and close the loop by turning production traces into new eval cases
  • Safety, Security & Guardrails: Enforce structured output and ground claims in citations, defend against prompt injection and tool abuse, detect and handle PII, and design retries and graceful degradation that prevent data leakage across users
  • Serving & Cost Optimization: Containerize and deploy agents with Docker and FastAPI, serve local and offline models, and apply measured token-level and caching optimizations to hit real cost and latency budgets

The program closes with a capstone, an end-to-end AI system you build, evaluate, and deploy, that becomes the centerpiece of your portfolio. Alongside it, you’ll get hands-on time with the tooling behind your Databricks Certified Generative AI Engineer Associate certification prep, plus AI cloud systems i.e. AWS Bedrock, AWS Sagemaker and/or VertexAI.

  • The Capstone: A real-world AI agent system built from problem framing through evaluation and production deployment
  • Certification Tooling: Hands-on practice with Databricks, CrewAI, and AWS Bedrock & SageMaker to prepare you for the Databricks Certified Generative AI Engineer Associate exam

Zindua your career in tech. Join our Applied AI Engineering course today!

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IMPACT

Our success in numbers

Our metrics reflect our commitment to high-quality education and the professional success of our students/graduates.

750+

Students Empowered

We’ve built a massive community of tech professionals in Kenya & beyond. 3,500+ empowered if inclusive of short courses

90%

Graduation Rate

Our industry-leading completion rate is a testament to our robust support system & engaging project-based curricula

#1

Top-Rated in Kenya

With a 4.9/5 star rating on Google reviews, we are the highest-rated coding school in in the region

Testimonials

Hear from our graduates

Real stories from our 1000+ alumni who are now leading the tech revolution in top companies worldwide.

  • My experience has been nothing short of amazing

    The curriculum is well-designed and covers all the essential topics in a comprehensive manner. The instructors are knowledgeable and passionate about teaching, and they go above and beyond to ensure that every student understands the material. The learning environment is collaborative and supportive, with plenty of opportunities to work on projects with other students. This has not only helped me to improve my coding skills but also to develop my teamwork and communication abilities.
    Januarius Kosgei
    Data Science Graduate 2023

  • Reliable technical mentors with excellent support

    I enjoy how the course work is structured, my Technical Mentor is super reliable and provides useful resources that compliment the course work I’m doing. The support from Zindua is excellent, they have a dedicated Slack channel where we ask and receive help from both the Technical Mentors and my fellow students. The projects are challenging but manageable and help reinforce the material covered. I would recommend Zindua to anyone who wants to kickstart their tech career and want a personalized learning experience. 
    Emelda Laeticia
    Software Dev Graduates 2023

  • Hard but exhilarating! Got the job I strove for 6 months in

    I started at Zindua with very limited knowledge about coding and I can now say 6 months later I have the job I strove for. The program was hard but exhilarating and I enjoyed almost all of it! The program is only 28 weeks and it is crammed full to teach you what you need to know both professionally and technically to land a job in the technical field. The program is a fantastic resource to help guide you in creating the best resume to practice interviews both behavioural and technical.
    Mesh Metho
    Data Science Graduate 2023

  • Practical exercises that helped reinforce the concepts covered

    The course content was comprehensive and covered a wide range of topics related to web development, including HTML, CSS, JavaScript, and responsive design. The content was well-structured, and the modules built upon each other in a logical and easy-to-understand way. Each module included quizzes and practical exercises that helped reinforce the concepts covered.
    John Kinyua
    Software Dev Graduate 2023

  • I felt like I was part of a larger network of motivated learners

    I had an incredible experience at this coding school! The curriculum was comprehensive and challenging, yet the instructors were always available to offer guidance and support. The community of students and alumni were incredibly supportive and encouraging, and I felt like I was part of a larger network of motivated learners. Overall, I feel confident and equipped to pursue a career in tech thanks to this school’s top-notch education and resources.
    BJay Mburu
    Software Dev Graduate 2023

  • Well-structured curriculum with real world projects

    The curriculum at Zindua School for Data Science program is well-structured and covers a wide range of topics, including statistics, machine learning, data visualisation, and data engineering. The curriculum is designed to be hands-on, with ample opportunities to apply the concepts learned through real-world projects and case studies. The school also offers elective courses to tailor the learning experience to individual interests, which I found to be a great feature.
    Lilian Ngugi
    Data Science Graduate 2023

Zindua your career in tech. Join our Applied AI Engineering course today!

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The Zindua Edge

What sets us apart from standard bootcamps & traditional universities

Discover the unique pillars that make Zindua the most trusted launching pad for tech professionals in Africa.

1

Personalised Mentorship

Small classes by design ensuring deep technical support and high-quality graduate output i.e. max 12 students for part-time/remote & max 17 for full-time

2

Advanced Tech Curricula

We go above and beyond standard bootcamps into technical fundamentals to set you apart i.e. AI-assisted coding, cloud systems, data structures & algorithms

3

Flexible Payment Plans

The most flexible pricing plans with numerous instalment options and Lipa mdogo mdogo where payments extend beyond the length of the program

1

Career & Placement Support

In-depth career development from profile building and technical interview prep to direct access to our employer networks

2

Project-based learning

Daily challenges, weekly projects, and capstones at every milestone ensuring you graduate with job-ready tech portfolio

3

Global cloud certifications

Program curricula anchored on AWS or Microsoft Azure, preparing you for globally recognised certifications

Financing

Choose the pricing option that best fits your needs

We offer the most flexible financing in the market; paying in fewer instalments guarantees you lower total fees.

One-time Upfront Payment

KES 5K deposit + KES 125K one-time fee; this totals to KES 130K – Cheapest Option

Pay in TWO Instalments

KES 5K deposit + KES 65K monthly for 2 months; this totals to KES 135K

Pay in THREE Instalments

KES 5K deposit + KES 45K monthly for 3 months; this totals to KES 140K – Most Popular

Pay in FOUR Instalments

KES 5K deposit + KES 35K monthly for 4 months; this totals to KES 145K

Pay in FIVE Instalments

KES 5K deposit + KES 29K monthly for 5 months; this totals to KES 150K

Flexi Payment Plan (Lipa mdogo mdogo)

KES 5K deposit + KES 13,500 monthly for 12 months. Payments will extend beyond the program length, therefore, we’ll require the student/parent (whoever will be making payments) to go through a credit vetting process by Chaptr Global. – Most Flexible

Zindua your career in tech. Join our Applied AI Engineering course today!

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Frequently Asked Questions

We have a three-step admissions process. Apply on website, attend a 15-minute interview, and pay the enrolment deposit to confirm your enrolment. Simple and straightforward. Since there could be some weeks between the time you pay the deposit and the orientation program, you’ll be invited to our Free Courses to start learning concepts that would be beneficial for your learning journey.

Yes, Zindua School has an enrolment deposit of KES 5,000 which is deductible from your program fees. The deposit allows us to confirm your slot in an upcoming intake. Fees will be paid (minus the deposit) once you have started the program.

Zindua School is extremely practical and our focus is on preparing our students for real-world problems in today’s job market. Most of our graduates get hired on the basis of their portfolio and this speaks to the quality of the skills you’ll gain at Zindua School.

Unfortunately, we do NOT offer a job guarantee. However, we do offer job placement support for graduates. This involves our career module where you’ll optimise your CV/resume, LinkedIn profile, portfolio, and even learn about technical interviews. Additionally, we do connect some of our graduates to our constantly growing employer networks.

For our full-time program, you’ll be expected to attend classes in-person on three weekdays and online on two weekdays. Classes run from 9am to 2pm, with take home coding assignments on each day. You are required to commit 35-40 hours weekly if you plan to join us full-time.

For our part-time program, you’ll be expected to attend online classes in the evening from Monday to Thursday. The online classes run for two hours and are slotted anytime from 6pm to 10pm based on your class group. You’ll have in-person classes on Saturdays from 10am to 2pm. You are required to commit 20-25 hours weekly to cover for class sessions and out-of-class projects. This is ideal for those with work or school commitments.

Note: full-time programs are shorter than the part-time program as there is more time committed per week for learning. However, both programs cover the same content and have the same expected outcomes.