AI & Machine Learningadvanced Level

Full Stack AI & LLM Automation Engineering

Build production-ready AI applications, OpenAI API workflows, RAG document search systems, and automated agent pipelines with Python and Next.js.

35 Estimated Hours 1 Modules (1 Lessons) Instructor: Bilal Ahmad

COURSE TUITION

FREE ACCESS

Full lifetime access
Practical lab assignments
Timed module quizzes
1-on-1 instructor manual code reviews
Verifiable completion certificate

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Course Overview

Learn how to engineer real AI products. This course covers prompt orchestration, text embeddings, vector databases (Pinecone / pgvector), Retrieval-Augmented Generation (RAG) pipelines, and building interactive web interfaces.

SYLLABUS MASTERY

What You Will Learn

Connect Python backends with OpenAI, Anthropic, and open-weight HuggingFace models.

Build high-accuracy RAG document querying pipelines using pgvector and embeddings.

Implement streaming responses and AI chatbots into Next.js React user interfaces.

Create autonomous multi-step AI agents with tool-calling capabilities.

Monitor token costs, rate limits, and implement latency caching.

STRUCTURED MODULES

Course Curriculum

1 Modules • 1 Lessons

Module 1

Module 1: Embeddings & Vector Knowledge Databases

1 Lessons

Lesson 1: Vector Embeddings & High-Speed Similarity Search

50 minFree Preview

Recommended Prerequisites

Intermediate Python proficiency.

Familiarity with REST APIs and JSON data handling.

Basic web frontend understanding.

INSTRUCTOR PROFILE

Bilal Ahmad

Lead Software Architect

Graduate from MUST University with 3+ years teaching computer science. Direct code reviewer for all student labs.

Accredited Certificate

Complete all module quizzes with an 80%+ passing score and submit the practical lab assignment to unlock your verifiable certificate.

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