Programmes — DeepLearnPath

DLP-101

Deep Learning Foundations Path

Fourteen-week guided path through neural network fundamentals, backpropagation, gradient descent, and PyTorch model training. Covers multilayer perceptrons, loss functions, optimisers, and introductory computer vision. C$1,950 – C$2,340. Prerequisites: Python fundamentals. Live cohort and self-paced units available from our Vancouver Pender campus.

Deep learning foundations cohort at DeepLearnPath

DLP-201

Generative AI & Diffusion Models Overview

Ten-week path exploring generative AI architectures, diffusion models overview, and practical creative AI projects. Includes ethical AI education and human verification of AI-assisted outputs. C$2,290 – C$2,750.

DLP-301

Large Language Models & Prompt Engineering

Twelve-week programme on transformer architecture, embeddings, fine-tuning concepts, RAG foundations, and prompt engineering with ChatGPT, Claude AI, and Google Gemini in professional context. C$2,450 – C$2,890.

DLP-401

Computer Vision with Neural Networks

CNN pipelines, image classification, object detection overview, and TensorFlow modules alongside PyTorch labs. Ten weeks, C$2,190 – C$2,620. Portfolio projects with instructor feedback.

DLP-501

NLP & Transformer Applications

Natural language processing, attention mechanisms, and transformer applications for text analytics and AI automation workflows. Eleven weeks, C$2,350 – C$2,790.

DLP-601

AI Career Development Capstone Path

Capstone integrating deep learning, generative AI, and model deployment overview into career portfolio deliverables. Eight weeks, C$2,590 – C$3,050. Certificate attests to participation — not job guarantees.

Capstone demo presentation at DeepLearnPath

DeepLearnPath delivers structured deep learning courses. Not an AI consulting firm or SaaS vendor.

Programme comparison guide

Choosing among six paths can feel overwhelming. Start with Deep Learning Foundations if you have fewer than six months of Python practice with data libraries. Choose Generative AI Overview if you understand basic supervised learning but have not yet trained sequence models. Select the LLM path when you must evaluate vendor APIs responsibly. Computer Vision and NLP paths assume completion of foundations or equivalent experience documented in a pathway advisory call.

The capstone path integrates skills from prior modules; most learners complete at least two programmes before enrolling. We do not enforce rigid locks, but instructors may recommend prerequisite work when lab submissions show gaps that will impede cohort peers.

Pricing and payment

Published ranges reflect early-bird cohort pricing versus standard enrolment. Corporate invoicing uses net-thirty terms for approved organisations. Taxes apply as required in British Columbia. Scholarships are limited and announced quarterly.

Materials and licensing

Syllabus PDFs, notebooks, and slide decks are licensed for personal learning during enrolment. Redistribution or posting complete modules on public repositories violates terms of use. You may showcase derivative portfolio work with attribution.

Enrolment, pacing, and support

Each programme lists whether it is cohort-paced or offers self-paced units with monthly check-ins. Cohort learners benefit from synchronized deadlines that create accountability; self-paced learners trade flexibility for additional written feedback cycles. Both formats include access to pathway advisors who help you interpret syllabus jargon—advisors coach learning plans, they do not write production code for your employer.

Assessment combines auto-graded exercises where appropriate and instructor-reviewed submissions where judgment matters. We emphasise reproducibility: seeds, environment files, and short methodology notes accompany every lab hand-in. Plagiarism and uncredited generative assistance violate academic integrity rules stated in enrolment agreements.

Accessibility accommodations are available when requested before start dates. Captioning, extended time on quizzes, and reserved seating in the studio are common arrangements. Contact [email protected] with specific needs so we can coordinate early.

Guided deep learning programmes