Advanced Certification in Applied Gen AI and Agentic Systems in Saudi Arabia

Master Generative AI, LLM-based AI Agents & Agentic systems

Learn from instructor-led sessions with real-world applications

Features a vast curriculum with 21 modules & capstone projects

Receive the advanced certificate in Applied Gen AI & Agentic Systems

Work with tools like ChatGPT, LangChain & AutoGPT

Ideal for IT professionals, students & entrepreneurs

Includes practical labs to build multimodal AI applications

Enjoy flexible learning that fits your personal schedule

Affordable payment choices available through instalments

4.85/5

5063 Enrolled

Overview

What our training includes:

Master deep learning techniques using Keras and TensorFlow
Build real-world NLP applications with ChatGPT and LangChain
Implement reinforcement learning using Q-learning and Grid-world agents
Develop AI agents using LangChain and AutoGPT frameworks
Create multimodal AI models using GPT-4V and CLIP
Fine-tune domain-specific LLMs for real-world applications

Learning Outcomes

Once you complete the training, you will be able to:

Create AI agents with LangChain, AutoGPT and CrewAI tailored for practical real-world applications

Master NLP techniques using ChatGPT, LangChain and transformer-based frameworks for advanced language processing tasks

Apply reinforcement learning through Q-learning, PPO methods and Grid-world simulations to solve dynamic problems

Build multimodal AI solutions integrating GPT-4V, CLIP and text-to-image models for innovative outputs

Generate synthetic images and datasets using GANs such as DCGAN and CycleGAN for diverse applications

Deploy autonomous AI solutions utilising CrewAI and LangGraph to deliver real-time intelligent performance

Ready to get started?

Prerequisites

Before enrolling in the Advanced Certification in Applied Gen AI and Agentic Systems in Saudi Arabia, the eligibility requirements are as follows:

Applicants should hold a B.E., B.Tec.h, M.E, M.Tech, M.Sc., MBA, or an equivalent master’s degree with at least 50% marks along with 1 year of professional work experience
Candidates with a BSc, BA, LLB, CA, or BBA must have secured a minimum of 65% marks and possess 2 years of relevant professional experience. For non-engineering graduates, a high school-level mathematics background is mandatory
Programming knowledge is required, with prior coding experience in Python being highly preferred

Overall ratings by our students

Upcoming sessions

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

Related courses

Curriculum

Why deep learning?
ANN structure, activation functions
Feedforward and backpropagation
Build ANN using Keras

TensorFlow 2.x and Keras API
Loss functions and optimizers
Overfitting and underfitting
Train a churn model on tabular data

NLP use cases: chatbots, sentiment, classification
Preprocessing: tokenization, stop words, lemmatization
Vectorization: Bag of Words, TF-IDF
Hands-on: Sentiment analysis

Logistic regression and Naive Bayes
Word embeddings introduction
Build: spam or feedback classifier

CNN layers: filters, pooling, convolution
Applications: image classification, document scan
Hands-on: Use pre-built CNN (transfer learning)

Save/load models (Pickle, Joblib, TF)
Create Flask/FastAPI REST APIs
Deploy a model (e.g., churn or sentiment)

Agent, environment, state, action, reward
Exploration vs exploitation
Q-learning (tabular)
Hands-on: Grid-world agent simulation

Self-attention and multi-head attention
BERT vs GPT
Positional encoding
Hands-on: Text generation with transformer

Generator vs Discriminator
DCGAN, CycleGAN, StyleGAN
Hands-on: Synthetic image generation

Denoising Diffusion Probabilistic Models (DDPM)
Diffusion vs GANs
Tools: Stable Diffusion, DALL·E
Hands-on: Generate text-to-image outputs

GPT, Claude, Falcon, Mistral overview
Prompt engineering
Fine-tuning domain-specific LLMs
Hands-on: Legal/Medical chatbot

LangChain architecture
Vector databases (FAISS, Pinecone)
Build RAG pipeline
Hands-on: Doc-aware Q&A chatbot

Vision-Language Models: GPT-4V, CLIP, BLIP
Text-to-image/video/audio generation
Hands-on: Generate media from prompts

Content generation pipelines
Brand asset generation
Tools: Sora, Runway, DALL·E

Deep Q-Networks (DQN)
Policy Gradients
PPO (Proximal Policy Optimization)
Hands-on: Train an autonomous agent

Multi-agent collaboration
LangChain dynamic decision agents
Build a simple autonomous assistant

Task decomposition & planning
Reflex vs learning agents
CrewAI orchestration
Hands-on: Multi-agent research + writing task

LangChain tools: Google Search, Wolfram, Zapier
Agent memory: vector, long-term, summary
Context retention strategies
Hands-on: Web-aware document chatbot

OpenAI, Claude function calling
ReAct prompting strategy
Toolformer concept
Hands-on: Reasoning assistant with tools & APIs

Orchestrating prompt → tools → output
Guardrails, observability
Evaluation metrics: latency, task completion
Hands-on: AI assistant to summarize meetings, update CRM, draft reports

Ethics, safety, bias, hallucinations
Gradio, Streamlit, Hugging Face Spaces
Hands-on: Host your GenAI app publicly

Project Brief: Build and deploy an end-to-end autonomous system powered by LLMs, LangChain agents, external tools, memory and reasoning strategies.

Deliverables:

LLM-powered task assistant with RAG
LangGraph + CrewAI agent orchestration
Integration with external tools/APIs (e.g., calendar, CRM, Google Search)
ReAct-based decision flow
Deployed on Streamlit or Hugging Face
Performance evaluation (task completion, responsiveness, hallucination %)

Example Themes:

Meeting summarizer + action item generator
Business intelligence research assistant
Autonomous marketing campaign writer
Project planner with goal decomposition

Frequently asked questions

The Advanced Certification in Applied Gen AI and Agentic Systems in Saudi Arabia is a specialised program designed to help you with cutting-edge expertise in artificial intelligence. Our course dives deep into generative AI, reinforcement learning, large language models (LLMs) and autonomous agentic systems. Unlike generic AI courses, it emphasises hands-on learning with tools like TensorFlow, PyTorch, LangChain, AutoGPT and CrewAI, which helps you to design, train and deploy intelligent systems effectively.

The program blends theory, applied projects and mentorship to help you master complex AI concepts while ensuring you can implement scalable and ethical AI solutions across sectors like IT, finance, healthcare. By completing this course, you position yourself as a future-ready AI leader in one of the fastest-growing digital economies in the world.

The Advanced Certification in Applied Gen AI and Agentic Systems in KSA is designed to give you hands-on expertise in building, deploying and managing AI-driven solutions. The program focuses on practical applications, industry tools and career readiness. These are some of the key highlights:

Comprehensive curriculum covering generative AI, reinforcement learning, agentic systems, multimodal AI and ethical AI practices
Hands-on projects using tools like TensorFlow, PyTorch, LangChain, AutoGPT & CrewAI
Industry-aligned learning structured around KSA’s goals to meet local and global market demands
Expert mentorship from certified AI professionals with global experience in cutting-edge research and enterprise deployments
Flexible learning modes with options for classroom, online live sessions, or blended formats
Career-focused training with resume workshops, interview preparation & job placement support in the AI sector

Yes, this course in KSA is structured to help the beginners in AI while also challenging professionals with prior experience. It starts with the fundamentals of machine learning, neural networks and Python programming. This ensures beginners gain the right foundation before moving to advanced topics.

As you progress, the training gradually introduces complex concepts like generative AI, reinforcement learning and agentic systems. With guided mentorship and hands-on projects, even beginners can confidently build real-world AI applications.

In the Advanced Certification in Applied Gen AI and Agentic Systems in KSA, you will gain hands-on experience with cutting-edge tools and frameworks widely used in AI and automation. These tools and technologies are:

LangChain, AutoGPT, CrewAI – for building AI agents and workflows
ChatGPT, Hugging Face Transformers – for advanced NLP applications
PyTorch, TensorFlow – for deep learning and model training
Q-learning, PPO, Grid-world – for reinforcement learning experiments
GANs (DCGAN, CycleGAN) – for creating synthetic data and images
CLIP, GPT-4V, Diffusion models – for multimodal AI and generative tasks
AWS & Azure AI Services – for scalable cloud-based deployment of AI solutions

Our training program goes beyond conventional AI training by focusing deeply on generative AI (Gen AI), large language models (LLMs) and autonomous agentic systems, the areas where many other certifications offer limited or no coverage. This is how it compares to others:

Specialised Focus – Unlike broader AI certifications (e.g., CAIP or data science) that cover general ML and analytics, our advanced certification course zeroes in on cutting-edge Gen AI and agentic workflows
Hands-on Autonomy – You gain practical experience building autonomous AI agents using tools like LangChain and AutoGPT, whereas other programs often focus more on foundational concepts or vendor-neutral ML
Industry Relevance – Designed with alignment to fast-growing AI ecosystem in KSA, it offers local applicability and real-world project experience

During the Advanced Certification in Applied Gen AI and Agentic Systems in KSA, you will gain hands-on expertise in building and deploying autonomous AI systems. The training emphasises practical application where you learn how to design AI agents that can make decisions.

Using tools like CrewAI and LangGraph, you will create multi-agent systems, integrate planning and reasoning strategies and develop agents capable of complex decision-making. The capstone project will allow you to deploy these systems in real-world scenarios.

Yes, you will be able to enrol in this Applied Gen AI and Agentic Systems course from locations outside Saudi Arabia. To maintain uniform training quality worldwide, we provide our Advanced Applied Gen AI course in several GCC areas.