Natural Language Processing (NLP)
NLP covers the full arc of language processing: from tokenisation and classical statistical methods through word embeddings to transformer-based models.
2 months Classroom & Online
View syllabus 6 modules
AI & Advanced Technologies
Artificial Intelligence (AI)
The whole field, in the right order.
The Artificial Intelligence program is the broad foundation track for the AI pillar. It covers the field as a whole — search and reasoning, machine learning, neural networks, computer vision, language, and the ethics and deployment questions that come with all of it.
3 months Classroom & Online Beginner to Intermediate 6 modules
Artificial Intelligence The whole field, in the right order.
Overview
What this course is, plainly
The Artificial Intelligence program is the broad foundation track for the AI pillar. It covers the field as a whole — search and reasoning, machine learning, neural networks, computer vision, language, and the ethics and deployment questions that come with all of it.
It is the right starting point if you know you want to work in AI but do not yet know which specialisation fits you. Finish here and the LLM, RAG, Agentic AI and Generative AI tracks all become straightforward next steps.
Why choose this course
- Broad, correctly sequenced foundation
- Python taught inside the course
- Covers vision, language and classical AI
- Ethics and responsible deployment included
- Clean path into every specialist AI track
Curriculum
Module-by-module syllabus
The same structure on every Xypron course page, so you can compare tracks like for like. Each module ends in working code, not a quiz.
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Module 1: AI Foundations
What the field actually contains, beyond the headlines.
- History & branches of artificial intelligence
- Intelligent agents & environments
- Search algorithms: BFS, DFS, A*
- Constraint satisfaction problems
- Knowledge representation & reasoning
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Module 2: Python for AI
The working language of the entire discipline.
- Python syntax & data structures
- NumPy array computation
- Pandas data handling
- Matplotlib visualisation
- Jupyter notebook workflow
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Module 3: Machine Learning Core
The statistical engine underneath modern AI.
- Supervised learning: regression & classification
- Unsupervised learning & clustering
- Model evaluation & validation
- Feature engineering
- Scikit-learn in practice
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Module 4: Neural Networks & Deep Learning
Where the last decade of progress came from.
- Perceptrons & multi-layer networks
- Backpropagation & optimisers
- Convolutional networks for vision
- Recurrent networks & attention
- TensorFlow / Keras fundamentals
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Module 5: Applied AI
The three application domains that dominate job listings.
- Computer vision: classification & detection
- Natural language processing essentials
- Recommendation systems
- Speech & audio basics
- Working with pretrained models
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Module 6: Ethics, Deployment & Capstone
The professional responsibility layer, treated seriously.
- Bias, fairness & dataset provenance
- Explainability & interpretability
- Privacy & data protection in AI systems
- Deploying a model as a service
- End-to-end capstone project
Projects you'll build
- Image classification system with a pretrained CNN
- Recommendation engine for a product catalogue
- Deployed AI service with an interpretability report
Roles this prepares you for
- AI Engineer
- Machine Learning Engineer
- AI Developer
- Data Scientist
Tools you'll master
Python 
NumPy 
Pandas 
Scikit-learn TensorFlow Keras OpenCV 
Jupyter Outcomes
What happens after the last module
The course does not end at the capstone. Placement support runs from your first mock interview until you have an offer — and it is support, not a guarantee.
Resume rewrite
Rebuilt around the projects you actually shipped here, targeted at the roles you are applying for.
Mock interviews
Technical and HR rounds with written feedback after each one, repeated until the gaps close.
Profile sharing
Your profile goes to our hiring partners with a note from the trainer who taught you.
Interview scheduling
We book the interviews and follow through until there is a decision either way.
Next step
Ask us anything about Artificial Intelligence (AI)
Batch timings, the fee, whether your background fits, what the trainer's day job is — all fair questions. A counsellor will call you back within two business hours.
Basic programming logic. Python is taught within the course, so this is a valid entry point into the AI pillar.
The course runs for 3 months in classroom & online mode. Weekday, weekend and evening batches are scheduled continuously — call +91 73493 01293 for the next available start date.
Image classification system with a pretrained CNN; Recommendation engine for a product catalogue; Deployed AI service with an interpretability report — plus an end-to-end capstone project you deploy yourself and can walk an interviewer through line by line.
Yes. Sit a full session with the trainer who would actually teach your batch before you decide anything. Ask for one on WhatsApp or through the enquiry form on this page.
Enquiry
Enquire about Artificial Intelligence (AI)
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Also in AI & Advanced Technologies
Compare with the neighbouring tracks
Large Language Models (LLM)
This track treats large language models as engineering material rather than magic. You learn how they are trained, why they fail the way they do, and how to build reliable products on top of something fundamentally probabilistic.
2 months Classroom & Online
View syllabus 6 modules
Retrieval Augmented Generation (RAG)
RAG is the pattern behind almost every enterprise AI deployment: retrieve the right context from your own data, then let the model answer from it. It is also the pattern most teams implement badly, and retrieval quality is almost always the reason.
6 weeks Classroom & Online
View syllabus 6 modules
Next step
Ready to start Artificial Intelligence (AI)?
Sit a free demo class before you commit. Ask about batch timings, the trainer, and exactly what the placement support covers.