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Advanced Certification in Applied Gen AI and Agentic Systems in Bahrain

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

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5193 EnrolledEnrolled Learners
GoogleGoogle4.85/5
5193 EnrolledEnrolled Learners

Overview

What will you learn from us:

  • 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

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

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.

Our Trainers

Learning Outcomes

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

  • 1

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

  • 2

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

  • 3

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

  • 4

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

  • 5

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

  • 6

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

  • 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

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    Frequently asked questions

    The Advanced Certification in Applied Gen AI and Agentic Systems is a specialised program designed to provide professionals with hands-on expertise in cutting-edge AI technologies. It covers advanced topics such as deep learning, natural language processing, generative AI and reinforcement learning. This prepares you to design intelligent and adaptive systems.
    Unlike generic AI courses, our program emphasises applied learning with real-world projects using tools like LangChain, AutoGPT and transformers. We enable you to build autonomous agents and multimodal AI systems that drive innovation across industries.

    The Advanced Certificate in Applied Gen AI and Agentic Systems will guide you in implementing AI in your backend applications by demonstrating how to construct AI agents with tools like LangChain and Autogpt. You will gain practical knowledge about complex tools such as TensorFlow, Keras, and reinforcement learning algorithms, enabling you to develop autonomous AI agents and multimodal apps that enhance your current projects and elevate your technical skills.

    As a business person, the Advanced Certification in Applied Gen AI and Agentic Systems will equip you with the hands-on skills to integrate generative AI and autonomous agents into your business processes. You'll gain skills in building AI models with ChatGPT, LangChain, and reinforcement learning, allowing you to develop tailored AI-powered applications that enhance your business functions, drive efficiency, and enhance customer experience.

    After completing the certification, you will gain practical experience in developing AI-powered solutions with tools such as LangChain, AutoGPT, and Crewai. You will also learn to fine-tune large language models (LLMs), utilise reinforcement learning, and create multimodal AI systems using technologies like GPT-4V and CLIP. The hands-on training enables you to apply these skills to real-world scenarios and develop autonomous AI agents that can reason and solve problems.

    Completing this certification broadens many career opportunities in the fast-expanding field of AI. Graduates are well-suited for roles such as AI Engineer, Data Scientist, Machine Learning Specialist, and AI Solutions Architect. With the skills to design, develop, and deploy advanced AI applications, you can work across various sectors, including IT, finance, healthcare, and more, enhancing job prospects and future career growth.

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