Recommender Systems Training in Gurgaon, Delhi

Recommender Systems

Innovative AI Recommendation Engine at your tips

Duration : 6 months Classes : 36 Days : Weekdays / Weekends

Overview
Curriculum
Pre-requisite
Review

You`ve seen automated recommendations everywhere - on Netflix`s home page, on YouTube, and on Amazon as these machine learning algorithms learn about your unique interests, and show the best products or content for you as an individual. These technologies have become central to the largest, most prestigious tech employers out there, and by understanding how they work, you`ll become very valuable to them.

Recommender systems are complex; There`s no recipe to follow on how to make a recommender system; you need to understand the different algorithms and how to choose when to apply each one for a given situation. This interdisciplinary subject draws heavily from Information Retrieval, Machine Learning, and Data Mining.

This training introduces the fundamental concepts, algorithms, and evaluation techniques behind modern recommender systems. Students will explore how personalized recommendations are generated using collaborative filtering, content-based methods, and hybrid approaches. The course emphasizes both theoretical foundations and practical implementation, enabling learners to build scalable recommendation engines for real-world applications such as e-commerce, streaming platforms, and social media.

Target Audience:-
- Data Analysts and Data Scientists
- AI / ML / DS - Engineers
- Computer science students
- IT Professionals looking to transition into AI
- Research Scholars and AI Enthusiasts
- IT roles focused on personalization and user experience

Learning Outcomes:-
- Understand the core concepts, functions, and applications of recommender systems
- Model user preferences and item characteristics
- Apply machine learning techniques to predict user behavior
- Evaluate recommender performance using metrics like precision, recall, and RMSE
- Address challenges such as cold start, scalability, and diversity
- Design, implement, and assess recommender systems using tools like Python, scikit-learn, and TensorFlow

Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training

Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas

- You need to have intermediate to advanced Python experience. You are familiar with object-oriented Programming. You can write nested for loops and can read and understand code written by others.

-Intermediate Statistics background. You are familiar with Probability.

-Intermediate knowledge of machine learning techniques. You can describe backpropagation, and have seen a few examples of Neural Network architecture (preferrably a recurrent Neural Network or a long short-term memory network).

-You have seen or worked with a Deep Learning framework like TensorFlow, Keras, or PyTorch before.

....

NB: All our trainings are always tailored to adopt to the Individual's Pace and Learning Depth.

NB: As a stepping stone, providing foundational knowledge, Bridge Courses are conducted periodically, to help students transition between different levels by closing knowledge gaps. These classes can be attended ad hoc, and are 'complimentary' for our bonafide students.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre and complete your registration.

This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.

Module 1: Introduction and Foundations
✔ Course Introduction
✔ Taxonomy of Recommender Systems
✔ Recommender Engine Framework
✔ Data for Recommender Systems, Explicit vs. Implicit Feedback
✔ Basic Metrics & Similarity

Module 2: Collaborative Filtering (CF) Methods
✔ Memory-Based CF
✔ Model-Based CF: Matrix Factorization(MF)
✔ Matrix factorization (SVD, ALS)
✔ Optimization for MF
✔ Limitations of Basic CF

Module 3: Content-Based and Knowledge-Based Systems
✔ Content-Based Filtering (CBF)
✔ User Profile Learning
✔ Knowledge-Based Systems

Module 4: Evaluation and Hybrid Approaches
✔ Evaluation Techniques
✔ Offline vs Online Evaluation
✔ Evaluation Metrics
✔ Hybrid Recommender Systems

Module 5: Advanced and Modern Topics
✔ Deep Learning for RS
✔ Neural Collaborative Filtering (NCF)
✔ Sequential and Session-Based RS
✔ Context-Aware Systems
✔ Advanced System Challenges
✔ Explainable Recommender Systems (XRS)

Module 6: Lab & Project Work
✔ Implementing similarity measures in Python
✔ Building a movie recommender using collaborative filtering
✔ Designing a hybrid recommender for an e-commerce dataset
✔ Capstone project: end-to-end recommender system deployment

NB:The curriculum is regularly subjected to updates, reflecting the latest industry trends & current technological advancements.

At Vyom Data Sciences, we aspire to provide the latest curriculum and most recent technology, as a standard component of all our trainings. Experts, with 25+ years of experience from USA, Europe and Australia, bring the best industry practices while designing and executing these trainings. All our trainers are Highly Qualified and Certified in their respective subject areas.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre.

Bhawana

Fabulous NLP + ML course

I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.

Harish

Excellent ML course!

The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.