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Advanced Certification in Applied Gen AI and Agentic Systems in Qatar

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

GoogleGoogle4.29/5
4774 EnrolledEnrolled Learners
GoogleGoogle4.29/5
4774 EnrolledEnrolled Learners

Overview

What you will master with us:

  • Gain hands-on expertise in deep learning using TensorFlow and Keras
  • Design practical NLP applications with tools like ChatGPT and LangChain
  • Apply reinforcement learning concepts using Q-learning and Grid-world agents
  • Build intelligent AI agents using frameworks such as LangChain and AutoGPT
  • Develop multimodal AI models with technologies like GPT-4V and CLIP
  • Customize and fine-tune LLMs for specialized, real-world industry use cases

Upcoming sessions

Curriculum

1

Why deep learning?

2

ANN structure, activation functions

3

Feedforward and backpropagation

4

Build ANN using Keras

1

TensorFlow 2.x and Keras API

2

Loss functions and optimizers

3

Overfitting and underfitting

4

Train a churn model on tabular data

1

NLP use cases: chatbots, sentiment, classification

2

Preprocessing: tokenization, stop words, lemmatization

3

Vectorization: Bag of Words, TF-IDF

4

Hands-on: Sentiment analysis

1

Logistic regression and Naive Bayes

2

Word embeddings introduction

3

Build: spam or feedback classifier

1

CNN layers: filters, pooling, convolution

2

Applications: image classification, document scan

3

Hands-on: Use pre-built CNN (transfer learning)

1

Save/load models (Pickle, Joblib, TF)

2

Create Flask/FastAPI REST APIs

3

Deploy a model (e.g., churn or sentiment)

1

Agent, environment, state, action, reward

2

Exploration vs exploitation

3

Q-learning (tabular)

4

Hands-on: Grid-world agent simulation

1

Self-attention and multi-head attention

2

BERT vs GPT

3

Positional encoding

4

Hands-on: Text generation with transformer

1

Generator vs Discriminator

2

DCGAN, CycleGAN, StyleGAN

3

Hands-on: Synthetic image generation

1

Denoising Diffusion Probabilistic Models (DDPM)

2

Diffusion vs GANs

3

Tools: Stable Diffusion, DALLĀ·E

4

Hands-on: Generate text-to-image outputs

1

GPT, Claude, Falcon, Mistral overview

2

Prompt engineering

3

Fine-tuning domain-specific LLMs

4

Hands-on: Legal/Medical chatbot

1

LangChain architecture

2

Vector databases (FAISS, Pinecone)

3

Build RAG pipeline

4

Hands-on: Doc-aware Q&A chatbot

1

Vision-Language Models: GPT-4V, CLIP, BLIP

2

Text-to-image/video/audio generation

3

Hands-on: Generate media from prompts

1

Content generation pipelines

2

Brand asset generation

3

Tools: Sora, Runway, DALLĀ·E

1

Deep Q-Networks (DQN)

2

Policy Gradients

3

PPO (Proximal Policy Optimization)

4

Hands-on: Train an autonomous agent

1

Multi-agent collaboration

2

LangChain dynamic decision agents

3

Build a simple autonomous assistant

1

Task decomposition & planning

2

Reflex vs learning agents

3

CrewAI orchestration

4

Hands-on: Multi-agent research + writing task

1

LangChain tools: Google Search, Wolfram, Zapier

2

Agent memory: vector, long-term, summary

3

Context retention strategies

4

Hands-on: Web-aware document chatbot

1

OpenAI, Claude function calling

2

ReAct prompting strategy

3

Toolformer concept

4

Hands-on: Reasoning assistant with tools & APIs

1

Orchestrating prompt → tools → output

2

Guardrails, observability

3

Evaluation metrics: latency, task completion

4

Hands-on: AI assistant to summarize meetings, update CRM, draft reports

1

Ethics, safety, bias, hallucinations

2

Gradio, Streamlit, Hugging Face Spaces

3

Hands-on: Host your GenAI app publicly

1

LLM-powered task assistant with RAG

2

LangGraph + CrewAI agent orchestration

3

Integration with external tools/APIs (e.g., calendar, CRM, Google Search)

4

ReAct-based decision flow

5

Deployed on Streamlit or Hugging Face

6

Performance evaluation (task completion, responsiveness, hallucination %)

7

Meeting summarizer + action item generator

8

Business intelligence research assistant

9

Autonomous marketing campaign writer

10

Project planner with goal decomposition

Meet your Trainer

Our Trainers

We, at Learners Point, take immense pride in our teaching methods and instructors. Our instructors are some of the best experts in their fields and employ a practical approach to learning. Many of them are globally recognised and have a diverse set of experience in their field of expertise. You are always sure to have the best in the industry as your teachers who are ready to guide you at every step and make the experience informative yet enjoyable. Apart from the focus on learning your chosen course, our instructors also encourage students to develop communication skills and interpersonal skills necessary to excel in the practical world.

Our cutting edge teaching methods make every program an immersive and productive experience for the learners. Our learning methods are research-driven and are continuously updated to stay relevant to present times as well as the future. You will enjoy practical applications of everything learned through theory and regular mock examinations to help monitor your progress. Our courses are led by an instructor in a classroom setup and we do offer online high-quality sessions as well for individuals. We also monitor the training sessions with a progress tracker to maintain high standards of instruction & ethics.

Our Trainers

Learning Outcomes

After you complete your training, you will be able to:

  • 1

    Build practical AI agents using LangChain, AutoGPT, and CrewAI for real-world use cases

  • 2

    Learn advanced NLP techniques with ChatGPT, LangChain, and transformer-based models for complex language tasks

  • 3

    Use reinforcement learning with Q-learning, PPO, and Grid-world environments to solve adaptive challenges

  • 4

    Create innovative multimodal AI systems by combining GPT-4V, CLIP, and text-to-image models

  • 5

    Produce synthetic data and visuals using GANs like DCGAN and CycleGAN for varied applications

  • 6

    Deploy autonomous AI systems with CrewAI and LangGraph to enable responsive, intelligent behaviors in real time

  • objective-image

    Ready to get started?

  • Learners Point Certificate

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

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    Prerequisites

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

    • Applicants should hold a B.E., B.Tech, 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

    Related courses

    Frequently asked questions

    Our Advanced Certification in Applied Gen AI and Agentic Systems in Qatar is a practical, industry-focused program that teaches you to design intelligent AI systems. It covers deep learning, generative AI, NLP, and reinforcement learning. Learners work on real projects using tools like LangChain, AutoGPT, and transformers, helping them build autonomous agents that solve real-world problems.

    You do not need a technical background. Our Applied Gen AI and Agentic Systems course helps you understand how Gen AI and agentic systems work so you can lead AI-powered product strategies. Participants learn how to map use cases, evaluate models like GPT-4V, and align AI features with customer value. We help you become a stronger cross-functional leader in AI product development.

    Our Advanced Certification in Applied Gen AI and Agentic Systems in Qatar gives you startup-ready AI skills. We include everything from building MVPs with AutoGPT to fine-tuning LLMs for niche use cases. Participants learn how to integrate APIs, design intelligent agents, and even develop multimodal prototypes. These capabilities will not only set your startup apart but also attract investors looking for innovative AI-based solutions.

    This training is ideal for IT professionals, tech students, and entrepreneurs interested in building applied AI systems. We help you learn how to develop intelligent agents, optimize large language models, and integrate tools like Zapier or Google Search. This program gives you the hands-on skills and project experience to excel in the AI industry.

    By the end of the course, individuals know how to build and deploy AI solutions using platforms like LangChain, CrewAI, and AutoGPT. You gain hands-on experience with LLM fine-tuning, reinforcement learning, and multimodal AI tools like GPT-4V and CLIP. These skills allow you to create intelligent agents capable of reasoning, automation, and complex problem-solving.

    Graduates are prepared for high-demand roles such as:

    - AI Engineer
    - Machine Learning Specialist
    - Data Scientist
    - AI Solutions Architect
    - AI Researcher

    Do you want to learn more about Learners Point Academy?

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