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Learn. Practise. Apply.

Traditional AI with GenAI
Course at LearnAI

Explore Python and mathematical foundations, Data preparation and exploration, Machine learning, Deep learning, Computer vision and NLP and further topics in the curriculum.

Online India & worldwideClassroom Learn at a branchHybrid Online + classroom
Branches: Hyderabad · Guntur · Kurnool
Online: USA, Canada, UK, Australia, New Zealand and Germany

Ask about your preferred mode, branch and upcoming batch.

Ask About This Course ↗View Curriculum ↓
Illustration of AI models and automation

Upcoming Traditional AI with GenAI batches

Contact LearnAI for the next batch. Ask on WhatsApp.

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11 modulesTopic-based curriculum
Learn and practiseExplore the supplied topics
3 training modesOnline · Classroom · Hybrid
Talk to LearnAIEnrolment and batch information
Understand the programme

Traditional AI with GenAI at LearnAI.

Explore Python and mathematical foundations, Data preparation and exploration, Machine learning, Deep learning, Computer vision and NLP and further topics in the curriculum.

Your willingness to learn comes first

Who can join?

Build new skills or upgrade your technology knowledge. LearnAI welcomes students pursuing a degree, graduates, working professionals and learners from relevant domains.

Basic computer knowledge

Basic computer knowledge is recommended to help you participate in practical learning.

Students and professionals

Join while pursuing a degree, after graduation, or to develop skills for your relevant domain.

No prior technology knowledge required

You can begin without previous knowledge of the course technology. Bring your interest and willingness to learn.

No age limit

Learners of all ages are welcome. Learners under 18 should enrol with a parent or guardian’s consent.

What you will study

Explore the learning areas.

Python and mathematical foundations

Python, NumPy, pandas; linear algebra, probability, statistics and calculus concepts used in modelling.

Data preparation and exploration

Cleaning, missing data, exploratory analysis, feature engineering, train-validation-test splits and leakage prevention.

Machine learning

Regression, classification, trees, ensembles, clustering and dimensionality reduction; metrics and hyperparameter tuning.

Deep learning

Neural networks, backpropagation, optimisation, regularisation, CNNs and sequence models.

Computer vision and NLP

Image classification, transfer learning, text preprocessing, text classification and embeddings.

Transformers

Attention, self-attention, positional representations, encoder and decoder architectures and tokenisation.

The complete learning path

Traditional AI with GenAI course curriculum.

Open a module to view its topics.

MODULE 01Python and mathematical foundations
  • Python, NumPy, pandas; linear algebra, probability, statistics and calculus concepts used in modelling.
MODULE 02Data preparation and exploration
  • Cleaning, missing data, exploratory analysis, feature engineering, train-validation-test splits and leakage prevention.
MODULE 03Machine learning
  • Regression, classification, trees, ensembles, clustering and dimensionality reduction; metrics and hyperparameter tuning.
MODULE 04Deep learning
  • Neural networks, backpropagation, optimisation, regularisation, CNNs and sequence models.
MODULE 05Computer vision and NLP
  • Image classification, transfer learning, text preprocessing, text classification and embeddings.
MODULE 06Transformers
  • Attention, self-attention, positional representations, encoder and decoder architectures and tokenisation.
MODULE 07Large language models
  • Pretraining and adaptation concepts, inference, context limits, prompting, structured outputs and model selection.
MODULE 08Retrieval-augmented generation
  • Document ingestion, chunking, embeddings, vector search, retrieval, reranking, grounded answers and citations.
MODULE 09LLM evaluation and safety
  • Retrieval and answer evaluation, hallucinations, prompt injection, privacy, bias and human review.
MODULE 10Fine-tuning and deployment
  • Fine-tuning concepts, parameter-efficient adaptation, model serving, APIs, cost and latency monitoring.
MODULE 11AI application project
  • Build and evaluate an AI application integrating a trained model or an LLM with a documented RAG workflow.
Choose how you learn

Traditional AI with GenAI training near you and online.

Online training

Join from India, the USA, Canada, UK, Australia, New Zealand and Germany. Confirm your batch and time-zone schedule.

Classroom training

LearnAI branches: Dilsukhnagar, Hyderabad; Gardens, Guntur; Main Road, Kurnool. Confirm this course, batch and exact address before visiting.

Hybrid training

Discuss combined online and classroom participation at your preferred branch. Confirm the delivery arrangements for your batch.

Ask LearnAI about prerequisites, fees and current batch availability.

Before you enrol

Traditional AI with GenAI course questions.

Review the curriculum and discuss your learning goals with LearnAI.

What does the Traditional AI with GenAI course cover?

Explore Python and mathematical foundations, Data preparation and exploration, Machine learning, Deep learning, Computer vision and NLP and further topics in the curriculum.

How can I view the Traditional AI with GenAI curriculum?

The curriculum above contains 11 topic-based modules. Open each module for its full topics.

Can I learn online or at a branch?

LearnAI offers online, classroom and hybrid modes. Branches are in Hyderabad, Guntur and Kurnool. Confirm course and batch availability with the team.

Discuss your learning goals

Ready to explore Traditional AI with GenAI?

Share your background, preferred training mode, branch or country, and time zone.

Mon–Fri · 9 AM–7 PM IST · +91 93900 23585 · info@learnai.co.in

Chat with LearnAI ↗
Explore the concepts visually

A visual look at the subject

Illustrative overviews. Refer to the curriculum for the topics included in your course.

Retrieval-augmented generation workflow illustration
Retrieval-augmented generation workflow · Open image to enlarge
Learn with professional guidance

Experienced trainers. Practical knowledge.

Working professionalsIndustry knowledge connected to practical learning
10+ yearsRelevant professional experience within our core trainer team
Experienced trainersGuidance for concepts, tasks and project work

LearnAI’s core trainer team is supported by additional and part-time trainers. Trainer assignments and relevant experience vary by course, branch, training mode and batch availability. Experience figures refer to professional experience, not years of teaching.

For your batch’s trainer details, contact LearnAI.

What your course includes

Course charges cover

  • Live classes with a trainer
  • Doubt sessions
  • Assignments
  • Exams
  • Recordings
  • Portal access
  • Project assignment
  • Project explanation

Complimentary services

  • Resume writing
  • Mock interviews
  • Interview preparation
  • 100% job assistance

Job assistance does not guarantee a job offer.

Learner experiences

Google reviews by students

Feedback related to this programme · Editorial summaries, with original Google sources.

★★★★★

ammu12 kaneti

Review summary: Values practical Generative AI explanations, project work and internship experience.

Read on Google
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