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Deepskilling Answers
Ask Deepskilling
Concise, citeable answers for learners, hiring managers, and teams evaluating our programmes—plus the GenAI and cloud concepts we teach.
Learning & concepts
What is retrieval-augmented generation (RAG)?
RAG combines a language model with a searchable knowledge store. At query time, relevant documents are retrieved and passed into the prompt so answers stay grounded in your data—without retraining the base model for every content change.
When should I fine-tune an LLM instead of using RAG?
Fine-tune when you need style, format, or domain behaviour the base model lacks—even with good retrieval. Prefer RAG when facts change often, citations matter, or you must keep proprietary knowledge outside model weights. Many production systems use both.
What is LoRA and QLoRA?
LoRA (Low-Rank Adaptation) trains small adapter matrices instead of full model weights, cutting compute and storage. QLoRA adds 4-bit quantization so those adapters can be trained on consumer or limited GPUs while preserving quality for many tasks.
How is AWS Bedrock different from Azure OpenAI?
Both are managed GenAI platforms. Bedrock emphasizes multi-model access (including Anthropic, Meta, Amazon) inside AWS. Azure OpenAI centers on OpenAI models with Microsoft identity, networking, and Azure AI tooling. Choice usually follows existing cloud estate, model needs, and compliance boundaries.
What does a system design interview for ML roles typically cover?
Expect requirements gathering, data/feature pipelines, training vs inference trade-offs, latency and cost budgets, monitoring, failure modes, and rollout strategy—not only model architecture diagrams.
Programmes & workshops
Are Deepskilling courses live or self-paced?
Core programmes run as live cohort sessions with scheduled labs, office hours, and reviews. Recordings and resources support catch-up. Capstones and workshops are facilitated sprints around your use case.
Do you offer AWS and Azure AI certification paths?
Yes. Catalog tracks include AWS AI Practitioner, Machine Learning Engineer Associate, Generative AI Developer Professional, Azure AI Fundamentals, Azure AI Engineer, and related cloud administrator/developer certifications.
What is a Deepskilling workshop or capstone?
A structured sprint where your team brings a proprietary problem; senior mentors co-design architecture and implementation. Strong outcomes can become internal case studies or co-authored whitepapers.
Who are Deepskilling programmes for?
Working engineers, data/ML practitioners, cloud architects, and executives who need decision frameworks for GenAI—plus students building portfolio-ready systems work.
Platform & resources
What is the AI Classroom / sandbox?
Browser-accessible labs for CUDA, workflows, and interactive exercises so learners practice without local GPU setup. Some labs are public demos; cohort labs unlock with enrolment.
Where can I find tutorials and technical guides?
Start at /learn for question-led definitions, /resources for curated materials, /blog for longer articles, and /compare for decision pages such as RAG vs fine-tuning.
Operations
How quickly do you respond to contact inquiries?
Most inquiries receive a reply within one business day. Strategy-call bookings use the scheduling flow on course and training pages.
Can you run private or custom schedules for teams?
Yes. Enterprise and team cohorts can request custom calendars, private sandboxes, and workshop scopes. Use “Book a strategy call” on a course page or the contact form.
In what languages are programmes delivered?
Primary delivery is English. Workshop facilitation for specific teams can be discussed during scoping.