Deep Learning

Industry  Ceritified Deep Learning Course

Description

Deep Learning is a specialized branch of Machine Learning inspired by the structure of the human brain. It uses Artificial Neural Networks (ANNs) with multiple layers to analyze complex data such as images, videos, speech, and natural language.

Overview

Deep Learning goes beyond traditional algorithms by enabling computers to learn directly from raw data. Instead of manual feature engineering, DL models automatically extract patterns using multi-layered neural networks.

👉 It powers today’s most advanced technologies—self-driving cars, face recognition, virtual assistants, healthcare diagnostics, and recommendation systems.

At iSignal Academy, our Deep Learning program helps you build expertise in

• Neural Networks & Deep Architectures
• Image Processing with CNNs
• Natural Language Processing with RNNs & Transformers
• Generative AI with GANs
• Model deployment in real-world applications

Pre-requisites

• Basic knowledge of Python programming
• Understanding of Linear Algebra, Probability, and Calculus
• Experience with data handling & visualization (NumPy, Pandas, Matplotlib

💰Course Fee: INR 19,999/- 🎉(Limited Time Offer: Flat 20% OFF for first 30 enrolments → 🔥INR 14,999/- only)

iSignal Academy Benefits

• Hands-on Projects & Real-time Assignments
• Expert Trainers & Industry Veterans
• Affordable Fees with Flexible Learning Modes
• Placement Assistance & Interview Preparation
• Industry-Accredited Certification

Detailed Course Content

Module 1: Introduction to Deep Learning

• Difference between ML & DL
• Biological vs Artificial Neural Networks
• Applications of DL in industry

Module 2: Fundamentals of Neural Networks

• Perceptron & Multi-Layer Perceptron (MLP)
• Activation Functions (ReLU, Sigmoid, Softmax, Tanh)
• Gradient Descent & Backpropagation
• Optimizers (SGD, Adam, RMSprop)

Module 3: Deep Neural Networks (DNNs)

• Building ANN models with TensorFlow/Keras
• Overfitting & Regularization (Dropout, L1/L2)
• Hyperparameter tuning

Module 4: Convolutional Neural Networks (CNNs)

• Image classification & recognition
• Convolution, Pooling & Filters
• Architectures: LeNet, AlexNet, VGG, ResNet
• Applications: Object detection, Face recognition, Medical imaging

Module 5: Recurrent Neural Networks (RNNs)

• Sequential data & Time Series
• RNN, LSTM, GRU architectures
• Applications: Sentiment Analysis, Text Generation, Stock Forecasting

Module 6: Natural Language Processing with Deep Learning

• Word Embeddings (Word2Vec, GloVe, BERT intro)
• Sequence-to-Sequence Models
• Attention Mechanism & Transformers
• Applications: Chatbots, Language Translation, Summarization

Module 7: Advanced Deep Learning Topics

• Transfer Learning & Pre-trained Models
• Reinforcement Learning (basics)
• Model Deployment with Flask, Streamlit, TensorFlow Serving
• Ethical AI & Explainability (XAI)

Module 8: Real-Time Projects & Capstone

• Image Classification (Cats vs Dogs)
• Sentiment Analysis on Tweets/Reviews
• Object Detection (YOLO/Faster R-CNN)
• Chatbot with RNN/Transformer
• GAN-based Image Generator
• Capstone Project: End-to-End AI Pipeline

Course Outcomes

• Master Core Concepts – Understand ML & DL fundamentals, algorithms, and neural networks.
• Work with Real Data – Collect, clean, and analyze datasets from multiple domains.
• Build ML/DL Models – Implement regression, classification, clustering, CNNs, RNNs, Transformers, GANs, and more.
• Hands-On Experience – Gain practical skills through real-time case studies and a capstone project.
• Use Industry Tools – Proficiency in Python, Scikit-learn, TensorFlow, Keras, PyTorch, and deployment tools.
• Solve Real-World Problems – Apply ML/DL techniques in Finance, Healthcare, E-commerce, and IoT.
• Model Deployment – Deploy ML/DL solutions using Flask, Streamlit, or cloud services.
• Career Growth – Build a strong portfolio on GitHub & Kaggle to showcase your projects.
• Job Readiness – Crack interviews with resume prep, mock interviews, and placement support.
• Future-Proof Skills – Step confidently into roles like ML Engineer, Deep Learning Engineer, Data Scientist, or AI Specialist.

Course Features

• Live Instructor-Led Classes – Interactive sessions with real-time doubt solving
• Real-Time Coding Assignments – Practice as you learn with hands-on coding tasks
• Internship & Placement Assistance – Gain industry exposure and secure job opportunities

Avarage Salary

📈 Deep Learning professionals are among the highest-paid in the AI/ML industry due to the rising demand for expertise in Neural Networks, Computer Vision, and Natural Language Processing.

• Entry-Level Package: ₹2.0 LPA – ₹4.0 LPA
• Mid-Level (1–3 Yrs Exp.): ₹6.0 LPA – ₹9.0 LPA
• Average Package: ₹6.0 LPA

👉 Monthly Takeaway: ₹32,857 – ₹34,129*

Career paths

• Entry-Level: Data Analyst, Junior ML Engineer
• Mid-Level: Machine Learning Engineer, AI Developer, Data Scientist
• Specialized Roles: Deep Learning Engineer, Computer Vision Engineer, NLP Engineer, Robotics Engineer
• Advanced Roles: Algorithm Engineer, Research Scientist, AI Architect, R&D in Wireless/VLSI/AI Systems

Course Highlights

• Mode: Online + Offline(Classroom)
• Duration: 6 Month (Instructor-led)
• Language: English
• Live Projects: 3 real-time projects
• Certification: Industry Recognized
• Career Support: Placement guidance + Interview preparation.
• Learning Mode: Blendid Learning ( Online Live With Classroom)

📲 Get a FREE Demo Session on Deep Learning – Just send “Hi” on WhatsApp 👉 7829450444

Interested in our Training? Fill out the enquiry form and our team will get back to you with details on fees, schedules, and offers.