School of TechnologyintermediateAI/MLPythonDeep Learning

AI & Machine Learning

Master neural networks, deep learning, and AI applications with hands-on projects

1,200+ students enrolled
Certificate included · 70% passing score

6 Months

Duration

12+

Live Projects

94%

Placement Rate

₹12L

Avg. Package

About This Course

Master neural networks, deep learning, and AI applications with hands-on projects. Build intelligent systems that solve real-world problems.

Learning Curriculum

A structured, project-driven syllabus designed by industry experts to make you job-ready.

Industry-Aligned Curriculum

Master every layer of modern development through interactive projects and real-world use cases.

5

Total Chapters

6 Months

Program Duration

01

Python for Data Science

  • Python Basics & Data Types20 minFree
  • Control Flow & Functions20 min
  • NumPy & Array Operations25 min
  • Pandas DataFrames30 min
  • Data Visualization with Matplotlib25 min
02

Machine Learning Foundations

  • What is Machine Learning?15 min
  • Linear Regression30 min
  • Classification with Logistic Regression35 min
  • Decision Trees & Random Forests30 min
  • Model Evaluation & Metrics20 min
  • Python & ML Quiz10 min
03

Deep Learning & Neural Networks

  • Introduction to Neural Networks25 min
  • Building Your First Model with Keras40 min
  • Convolutional Neural Networks (CNNs)35 min
  • Recurrent Networks & LSTMs30 min
  • Transfer Learning & Fine-Tuning30 min
  • Deep Learning Quiz10 min
04

Natural Language Processing

  • Text Preprocessing & Tokenization25 min
  • Word Embeddings & Word2Vec30 min
  • Sentiment Analysis Project45 min
  • Transformers & Attention Mechanism35 min
05

AI in Production

  • ML Pipelines with Scikit-learn25 min
  • Model Serialization & APIs30 min
  • Deploying ML Models with Flask35 min
  • Monitoring & Model Drift20 min
  • Capstone: End-to-End ML Project45 min

Meet Your Instructors

Learn from industry professionals with real-world expertise.

Sanjay Mehta

Head of Curriculum — Engineering

Skillytics

Sanjay ensures every module aligns with real industry workflows. He bridges the gap between academic theory and shop-floor practice.

LinkedIn

Kavitha Nair

Placement Lead — Core Engineering

Skillytics

Kavitha partners with 300+ manufacturing firms to connect our graduates with the right roles. She runs mock interviews and portfolio reviews.

LinkedIn

Rajesh Kulkarni

Senior Design Engineer

Tata Motors

Rajesh has 12+ years of experience in automotive product design at Tata Motors, Mahindra, and L&T. He has mentored over 5,000 aspiring mechanical engineers and led design teams on production vehicles.

LinkedIn

Technologies You'll Master

Master the most in-demand tools and technologies used by top companies.

Python

TensorFlow

PyTorch

Scikit-Learn

Keras

Hugging Face

OpenCV

Docker

Jupyter

AWS

Career Opportunities

Jobs You Can Apply For

+42% growth

ML Engineer

₹10-30 LPA

Build and deploy production ML models and pipelines.

+45% growth

AI Research Scientist

₹12-35 LPA

Advance AI capabilities through novel research and experimentation.

+40% growth

Deep Learning Engineer

₹10-28 LPA

Design and train neural networks for computer vision, NLP, and more.

+38% growth

NLP Engineer

₹10-25 LPA

Build text understanding, generation, and conversational AI systems.

+36% growth

Computer Vision Engineer

₹10-28 LPA

Create systems that understand and process visual information.

+35% growth

AI Product Manager

₹15-40 LPA

Lead AI product strategy and bridge business needs with ML capabilities.

What Our Students Say

Hear from learners who transformed their careers with this course.

"The deep learning modules were exceptional. I built a real-time object detection system as my capstone — it impressed the interviewers at Amazon and I got the offer."

Karthik Menon

Amazon

"Coming from a statistics background, this course bridged the gap to applied AI perfectly. The mentors helped me transition to an ML engineer role at Microsoft."

Divya Krishnan

Microsoft

Frequently Asked Questions

Everything you need to know before you start.

01Do I need a math background?

Basic familiarity with linear algebra and statistics helps, but we cover all mathematical foundations needed. A willingness to learn is more important than prior math expertise.

02What projects will I build?

You'll build 12+ projects including image classifiers, chatbots, recommendation systems, generative AI applications, and a capstone deploying a full ML pipeline to production.

03Is Python experience required?

No, we start with Python fundamentals. However, basic programming experience in any language will accelerate your learning.

04How is this different from the Data Science course?

This course focuses deeper on neural networks, deep learning architectures, and AI engineering. Data Science focuses more on analytics, visualization, and statistical modeling.

Master AI & Machine Learning

Join 1,200+ students who have transformed their careers with this program.