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AI/ML 24-Weeks

🎯 Suitable For: Developers, ML/AI engineers, tech leads, researchers aiming for deep expertise

📚 Course Type: Advanced, hands-on, theory-to-production

🌐 Mode: Live Online Sessions (2×2 hrs/week)

Module 0: Python

Module 1: Foundations & Workflow

Module 2: Data Preparation & Feature Engineering

Module 3: Supervised Learning

Module 4: Model Evaluation & Selection

Module 5: Unsupervised Learning

Module 6: Deep Learning Fundamentals

Module 7: CV with CNNs

Module 8: Natural Language Processing

Module 9: Generative Models

Module 10: MLOps

Module 11: Responsible AI

Capstone Project

Delivery : ONLINE- Live classes

Or AT INSTITUTE (Pune) - Face to face

Batch strength: 25 students per batch

Timeline : 24 weeks

Schedule : 2hrs/2 times a week (96 Hrs)

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48 weeks -Evolve AI & Data Science Architects Program

CoMPREHENSIVE - Foundation +AI & ML

Suitable for Professionals with a technical background seeking a career change or skill upgrade

Python Foundations (1–6 wks): Python, NumPy, Pandas, Matplotlib, Git/GitHub → Projects: EDA (Iris/Wine), Titanic survival prediction.

Math Foundations (7–24 wks): Linear Algebra, Probability, Statistics, Calculus, Optimization, Algorithms → Projects: Linear algebra ops, probability simulations, gradient descent from scratch.
Statistical ML (25–36 wks): Supervised (Regression, SVM, Trees, kNN), Unsupervised (Clustering, PCA), Ensembles (RF, Boosting), Model evaluation → Projects: Housing regression, fraud detection, churn prediction, recommendation engine, business case studies.
Deep Learning (37–48 wks): Perceptrons, Backprop, Gradient Descent, PyTorch, CNNs, RNNs/LSTMs, Transformers → Projects: MNIST & CIFAR-10 vision tasks, NLP (sentiment, NER), time-series forecasting, BERT fine-tuning.
Capstone Project: End-to-end ML/DL solution (e.g., medical image classification, NLP automation, production-scale recommender system).

Batch strength: 25 students per batch

Timeline : 48 weeks

Schedule : 2 times a week

Delivery : ONLINE- Live classes

Or AT INSTITUTE (Pune) - Face to face

Batch strength: 25 students per batch

Schedule : 2hrs/2 times a week (192 Hrs)

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24 Weeks Core Foundations essentials for AI ml

Course type - Foundation - Suitable for beginners who are just learning to code.

1.Python Foundations for Math and ML

2. Mathematical Foundations

3. Algorithms for ML Preparation

4. Optimization Methods

5. Programming Practice & Projects

6. Git & Version Control

7. Additional Concepts

Batch strength: 20 students per batch

Timeline : 24 weeks

Schedule : 2 times a week

Delivery : ONLINE- Live classes

Or AT INSTITUTE (Pune) - Face to face

Batch strength: 25 students per batch

Timeline : 24 weeks

Schedule : 2 times a week

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Python advanced course

Course type - ADVANCED - Suitable for coders who have basic knowlege of coding in python.

·Testing, logging, documentation and benchmarking

· SymPy, RegExp

· REST API access

· OpenAPI and Dall-E API access

· Object-Oriented Python

Batch strength: 20 students per batch

Timeline : 12 weeks

Schedule : 3 times a week

Real live project Internships with the industry!

Delivery : OFFLINE - AT INSTITUTE - Face to face

Tuition Fee : INR 35000 + Taxes

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10 DAYS MONEY BACK GURANTEE !!

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Algorithms + Data Structures = Programs

Course type - ADVANCED

· Sorting and Searching

· Scientific computation

· Union-Find

· Greedy Algorithms and Dynamic Programming

· Graph Algorithms

· Hashing

Batch strength: 20 students per batch

Timeline : 12 weeks

Schedule : 3 times a week

Real live project Internships with the industry!

Delivery : OFFLINE - AT INSTITUTE - Face to face

Tuition Fee : INR 35000 + Taxes

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Python for AI and ML 12 week

🎯Suitable For: Beginners and software professionals exploring AI/ML for the first time

📚 Course Type: Foundational, hands-on,

🌐 Mode: Live Online Sessions (2×2 hrs/week)

Module 1: Python Syntax and Semantics

Module 2: Conditionals and Iterations

Module 3: Collections

Module 4: Functions

Module 5: Libraries

Module 6: NumPy

Module 7: Matplotlib

Module 8: Pandas

Tuition Fee : INR 35,000 + Taxes

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AI Advanced Applications

Course type - ADVANCED- Suitable PROFICIENT CODERS

MNIST

IRIS

Titanic

House Price Prediction

Batch strength: 20 students per batch

Timeline : 12 weeks

Schedule : 3 times a week

Real live project Internships with the industry!

Delivery : OFFLINE - AT INSTITUTE -Face to face

Tuition Fee : INR 35000 + Taxes

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10 DAYS MONEY BACK GURANTEE !!

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Foundations of AI

Course type - Foundation - Suitable for STUDENTS WITH BASIC KNOWLEDGE OF PYTHON.

Foundational statistics

· Logistic Regression, Linear Discriminant Analysis, KNN

· Support Vector Machines, Kernel methods

Decision Trees, bagging and boosting

Batch strength: 20 students per batch

Timeline : 12 weeks

Schedule : 3 times a week

Real live project Internships with the industry!

Delivery : OFFLINE - AT INSTITUTE -Face to face

Tuition Fee : INR 35000 + Taxes

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Foundations of Machine Learning

Course type - Foundation - for coders

· · Perceptron

· Neural Networks

Deep Neural Networks

· Autoencoders

· Batch strength: 20 students per batch

Timeline : 12 weeks

Schedule : 3 times a week

Real live project Internships with the industry!

Delivery : OFFLINE - AT INSTITUTE -Face to face

Tuition Fee : INR 35000 + Taxes

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AI & ML Essentials for Technical Leaders

Course type - Suitable for Team Leads, Project Managers, and Technical Decision-Makers.

Guide your team effectively

 Make informed technical decisions

 Communicate confidently with clients

This course is tailored for technically proficient professionals seeking a solid understanding of AI and ML — without diving into complex implementation.

Introduction to Python-Basic to advanced

Setting up your development environment (IDE).
Exploring Python syntax and structure.
Understanding key libraries such as NumPy, Pandas, and Matplotlib.
Building familiarity to read, modify, and discuss code with your team.

AI & ML through Guided Code Demonstrations

Interactive Jupyter notebooks with implementations of essential AI and ML techniques, including:
- Classification (kNN, SVM).
- Clustering.
- Decision Trees.
- Different Neural Network architectures
Experimentation with key parameters to understand model behavior.
Discussions on results, interpretations, and real-world relevance.
Add additional libraries to your repertoire, such as scikit-learn and pytorch

Client Use Case Discussions

Analyzing real-world challenges from your own projects.
Exploring how AI and ML can address business objectives.
Collaborative discussion on solution design, feasibility, and risks.

Batch strength: For a minimum batch of 5 employees.

Timeline : 12 weeks

Schedule : 6 hours a week

Delivery : Online/Offline -Hybrid

Tuition Fee : INR 75,000 + Taxes

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