Applied AI for Software Developers Certification in Dubai

Upcoming sessions

Curriculum

1

**Install:** VS Code LLM plugins, Postman, LangChain/Transformers libraries

2

**Setup:** API keys (OpenAI, Hugging Face, Gemini)

3

**Test:** Minimal “Hello LLM” prompt-response from terminal & playground

4

**Hands-on:** Create a CLI tool that consumes an LLM prompt via API

1

Real-world architecture patterns:

2

Prompt → API → UX, Prompt → VectorDB → Context → Output

3

Understanding Model Capabilities: Reasoning, Creativity, Memory

4

Responsible AI: Model trustworthiness, hallucination handling

1

RESTful APIs: OpenAI, Gemini, Cohere, Claude

2

Rate limits, token management, API costs

3

Prompt composition in code (Python/JS)

4

Response parsing and retry logic

5

Streaming vs synchronous models

1

Prompt templates, chaining, few-shot prompting

2

Zero-shot vs prompt tuning vs fine-tuning: When to use what

3

Prompt structure: Inputs, Instructions, Examples, Format hints

4

Output validation using regex/schema (Pydantic)

1

LangChain: Chains, Agents, Memory

2

LlamaIndex: Document loaders, indexes, query engines

3

Tool/agent orchestration vs simplicity tradeoffs

4

Connecting data: PDFs, SQL, Web Pages

1

Embeddings explained: cosine similarity & search

2

Tools: OpenAI embeddings, Hugging Face, Instructor

3

Vector DBs: ChromaDB, Pinecone, Weaviate – which one and why?

4

Chunking strategies, metadata filters, scoring strategies

5

Evaluation: Recall, relevancy, hallucination control

1

Frontend-first vs API-first vs CLI-first strategies

2

Streamlit: Fast UIs for internal demos

3

Gradio: Interactive models for PoCs

4

FastAPI: Secure, scalable, testable endpoints

5

Bonus: Dockerization + CI/CD tips for AI apps

1

LoRA, PEFT, QLoRA – tuning without burning your GPU

2

Hugging Face: Model hub, datasets, trainers

3

Fine-tune vs. Retrieval-Augmented vs. Prompt Templates

4

Budgeting: Compute cost vs performance gain

5

Deployment options: AWS, Hugging Face Inference, GCP

1

Integrating LLMs in React apps using OpenAI SDK

2

Flutter AI workflows: Dart + HTTP + Cloud APIs

3

Prompt UX patterns: dynamic autofill, summarizers, assistants

4

Edge computing for AI (e.g., Ollama, Mistral on device)

1

Token budgeting: Prompt cost per feature pattern

2

Monitoring LLM APIs: Logs, quality metrics, latency

3

Bias, hallucination, and harmful response filters

4

Model comparison (GPT-4 vs Claude vs Cohere vs Mistral)

5

Cost control patterns: Dynamic model fallback, temperature tuning

1

Resume Matcher: RAG-based resume-to-JD matcher

2

Code Annotator: JS plugin for live code explanations

3

AI Doc Assistant: Open-source markdown doc Q&A bot

4

Dev CLI Agent: Chat-style AI CLI command generator

5

Copy Generator: AI for personalized product copywriting

6

Enable CI/CD for AI pipelines, add A/B prompt testing, or deploy via Hugging Face Spaces

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

Upon finishing the training, you will:

1

Gain expertise in LangChain and LlamaIndex to develop AI-driven applications and tools

2

Implement RAG systems and vector embeddings to optimize AI model efficiency and performance

3

Master the fine-tuning of models using PEFT and Hugging Face for tailored AI solutions

4

Acquire practical experience working with the OpenAI API to build scalable AI applications

5

Design innovative AI solutions through prompt engineering, model optimization, and effective API management

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KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

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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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Frequently asked questions

The Applied AI for Software Developers Certification in Dubai is a specialized program designed to teach developers how to integrate AI technologies into their software projects. It covers tools like LangChain, LlamaIndex, and OpenAI API, and teaches you to develop scalable AI solutions such as summarizers and RAG systems. The certification provides practical, hands-on experience, preparing you for real-world AI challenges and boosting your career in AI development.

Unlike other certifications that focus solely on theoretical concepts, the Applied AI for Software Developers Certification emphasizes practical, hands-on experience in AI application. Competitors offer introductory AI courses, but our certification ensures you can implement AI solutions directly in your development projects.

The Applied AI for Software Developers Certification in Dubai stands out for its hands-on, project-based approach, which focuses on real-world AI applications. Unlike some other certifications, it offers in-depth learning of LangChain and LlamaIndex, which are not typically covered in other programs. This practical focus ensures graduates are prepared for immediate application in AI development roles.

You will learn to work with a range of advanced AI tools and technologies, including LangChain, LlamaIndex, OpenAI API, Hugging Face, and PEFT. These industry-standard tools are crucial for building and fine-tuning AI applications, ensuring you gain relevant and up-to-date skills applicable to current AI projects.

Upon completing the Applied AI for Software Developers Certification in Dubai, you can pursue roles such as:

AI Developer: Create AI-driven applications
Machine Learning Engineer: Build and optimize machine learning models
Data Scientist: Analyze data using AI techniques
AI Solutions Architect: Design AI solutions for businesses

The certification is recognized globally, and its value extends beyond the UAE. It is respected by employers in the AI and tech industries worldwide, offering you a strong credential that enhances your employability in international markets and ensures you’re well-equipped for a global career in AI development.

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