Course Curriculum

Overview Curriculum Instructor Reviews FAQs

Learning goals

Build and train neural networks from scratch in Python.
Master TensorFlow, PyTorch and scikit-learn workflows.
Fine-tune large language models and generative AI
Build a career-ready portfolio of 8 deployed projects.
Deploy machine learning models to production with MLOps
Work with real datasets: cleaning, features and pipelines
Evaluate models with the right metrics and validation
Understand the math behind gradient descent and backprop

Skills you'll gain

Python TensorFlow PyTorch Deep Learning MLOps Data Wrangling NLP Model Deployment Generative AI Computer Vision

Course description

This comprehensive program takes you from the fundamentals of machine learning to building and deploying production-grade AI systems. You'll write real code from day one — training models, tuning hyperparameters and shipping them to the cloud.

Through 12 modules and 8 capstone projects, you'll develop the intuition and practical skills employers look for. By the end you'll have a portfolio of deployed AI applications and a recognized certificate to prove it.

Requirements

Basic programming knowledge (any language) is helpful but not required
A computer with internet access — no expensive GPU needed
Curiosity and willingness to build hands-on projects

Intended audience

Aspiring ML engineers who want a structured, project-based path
Developers looking to add AI skills to their toolkit
Data analysts moving into machine learning roles
Students and career-changers building a portfolio

6 programmes · Foundation to advanced learning

01 AI for Content Strategy & Digital Innovation Foundation Module: 3 months · Advanced Module: 3 months

Foundation Module — 3 months
Advanced ChatGPT & prompt engineering techniques
AI scriptwriting & narrative generation
Custom GPT development & audience research analytics
Visual design, asset generation & editing with AI
Introduction to workflow automation
Programme Completion Certificate / AI Master Recognition
Advanced Module — 3 months
No-code automation architecture
AI-driven social media management systems
Autonomous direct messaging & content repurposing agents
Enterprise n8n workflow automation
Programme Completion Certificate / AI Master Recognition

02 Enterprise Business Intelligence & Automation Architecture Analytics Foundation: 3 months · Advanced Engineering: 3 months

Analytics Foundation — 3 months
AI & machine learning fundamentals
Advanced prompt engineering for business data
Business data processing with advanced Excel
Interactive dashboards & business intelligence with Power BI
AI integration strategies for corporate workflows
Target global certification: Microsoft Certified
Advanced Engineering — 3 months
Database management with SQL
Custom Large Language Model (LLM) API integrations
Advanced n8n workflow & data orchestration
End-to-end enterprise automation pipelines
Industry Job-Ready Professional Certificate

03 NextGen AI & Technology Foundations Essentials Level: 3 months · Advanced Level: 4 months

Essentials Level — 3 months
General AI and technology foundations tailored to school and university students.
Certificate of Achievement
Advanced Level — 4 months
Advanced student AI learning. Contact admissions for the detailed module outline.
Advanced AI Practitioner Certificate

04 Advanced AI & Machine Learning Engineering Program Level 1: Foundations of Machine Learning: 4 months · Level 2: Deep Learning & Neural Architectures: 6–8 months · Level 3: Enterprise Generative AI & MLOps Engineering: 6 months

Level 1: Foundations of Machine Learning — 4 months
Applied mathematics & statistics for AI
Classical machine learning algorithms & predictive modelling
Level 2: Deep Learning & Neural Architectures — 6–8 months
Advanced database engineering with SQL
Deep learning frameworks with PyTorch
Multi-Layer Perceptrons (MLP) & neural networks
Autoencoders & unsupervised learning
Modern transformer architectures & attention mechanisms
Industry capstone project
Target global certification: Harvard Data Science & Machine Learning Certificate
Level 3: Enterprise Generative AI & MLOps Engineering — 6 months
Applied generative AI & Large Language Models
Retrieval-Augmented Generation (RAG) architecture
Autonomous multi-agent systems
Containerisation with Docker
Orchestration & cloud deployment with Kubernetes
Target global certifications: NVIDIA Certified Associate; Databricks Certified Generative AI Engineer; Microsoft Certified; Certified Docker Associate / Kubernetes

05 Python for Machine Learning & Data Science Python for ML & Data Science: 3 months

Python for ML & Data Science — 3 months
Python programming for numeric computing
Data analysis pipelines
Data visualisation
Preparing data for machine learning algorithms
Python for ML Specialist Certificate

06 Modern Full-Stack Web Architecture Modern Full-Stack Web Architecture: 5 months

Modern Full-Stack Web Architecture — 5 months
Frontend frameworks
Backend API construction
Database architecture
Full-stack project deployment
Full-Stack Web Developer Certificate

Meet your instructor

Emmielar Josan

Lead AI Engineer & Educator

4.9

Rating

18,204 Reviews

142K Student

24 Course

Emmielar is a Lead AI Engineer with over a decade building machine learning systems at scale. He has trained 140,000+ students worldwide and specializes in making complex.

Student reviews

4.9

3,214 ratings

86%

10%

Brooklyn Simmons

2 weeks ago

“The platform transformed complex analytics into simple actions, helping our team make faster, smarter deep technical expertise daily.”

Cody Fisher

1 weeks ago

“Our team reduced manual reporting time drastically and now focuses on strategy instead of repetitive data tasks thanks to AI insights.”

Jenny Wilson

1 month ago

“We improved marketing performance significantly using AI-driven recommendations that optimize campaigns, consistent results.”

Bessie Cooper

2 months ago

“The platform transformed complex analytics into simple actions, helping our team make faster, smarter deep technical expertise daily.”

Frequently asked questions

Q1. Can I host live coaching sessions?

Clients can view your availability, choose a suitable time slot, and book sessions online through the built-in scheduling system. Organize and manage all your projects effortlessly in one place. From initial planning to the finalized. Organize and manage all your projects effortlessly.

Q2. How do clients book coaching sessions?

Q3. Can I sell courses and coaching programs?

Q4. Does the platform support progress tracking?

05. Do I need technical skills to get started?