🚀 Course Overview

Deep Learning Fundamentals হলো একটি 45 Hours Comprehensive & Project-Based Course, যেখানে আপনি Deep Learning-এর মৌলিক ধারণা থেকে শুরু করে Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) এবং আধুনিক Deep Learning Techniques হাতে-কলমে শিখবেন।

বর্তমানে Deep Learning ব্যবহার হচ্ছে Computer Vision, Natural Language Processing (NLP), Image Recognition, Speech Recognition, Medical AI, Autonomous Vehicles, Recommendation Systems এবং বিভিন্ন AI-powered Applications-এ। এই কোর্সে আপনি Python, TensorFlow, Keras, NumPy, Pandas এবং অন্যান্য জনপ্রিয় Deep Learning Framework ব্যবহার করে Real-world Projects তৈরি করবেন।

Theory-এর পাশাপাশি Practical Implementation-এর উপর বিশেষ গুরুত্ব দেওয়া হয়েছে, যাতে আপনি Industry-ready Deep Learning Skills অর্জন করতে পারেন।

Basic Python Programming & Machine Learning Knowledge Recommended.

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📚 Course Information

• Course Name: Deep Learning Fundamentals
• Duration: 45 Hours
• Level: Intermediate
• Language: Bangla + English
• Class Type: Online / Offline
• Prerequisite: Basic Python Programming & Machine Learning Knowledge
• Hands-on Practice: Yes
• Real-world Projects: Yes
• Certificate: Yes

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🎯 What You’ll Learn

এই কোর্সে আপনি শিখবেন—

✅ Introduction to Deep Learning

✅ Artificial Neural Networks (ANN)

✅ Forward & Backpropagation

✅ Activation Functions

✅ Loss Functions & Optimizers

✅ TensorFlow & Keras

✅ Convolutional Neural Networks (CNN)

✅ Image Classification

✅ Recurrent Neural Networks (RNN)

✅ Sequence & Time Series Data

✅ Model Training & Evaluation

✅ Hyperparameter Tuning

✅ Transfer Learning Basics

✅ Model Saving & Deployment Basics

✅ Real-world Deep Learning Projects

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📖 Course Modules

Module 1 – Introduction to Deep Learning

• What is Deep Learning?
• AI vs Machine Learning vs Deep Learning
• Deep Learning Applications
• Neural Network Basics

Module 2 – Artificial Neural Networks (ANN)

• Perceptron
• Multi-layer Neural Networks
• Forward Propagation
• Backpropagation
• Gradient Descent

Module 3 – TensorFlow & Keras

• TensorFlow Fundamentals
• Building Your First Neural Network
• Keras API
• Model Training
• Model Evaluation

Module 4 – Computer Vision with CNN

• Introduction to CNN
• Image Classification
• Convolution & Pooling
• Transfer Learning
• Image Data Augmentation

Module 5 – Sequence Models

• Introduction to RNN
• LSTM Basics
• GRU Basics
• Time Series Forecasting
• Text Sequence Processing

Module 6 – Model Optimization

• Hyperparameter Tuning
• Regularization
• Dropout
• Batch Normalization
• Performance Improvement

Module 7 – Deployment & Best Practices

• Saving & Loading Models
• Model Inference
• Deployment Basics
• AI Ethics
• Deep Learning Best Practices

Module 8 – Real-world Projects

• Image Classification System
• Handwritten Digit Recognition
• Face Mask Detection (Concept)
• Sentiment Analysis (Basic)
• Time Series Prediction
• Final Deep Learning Capstone Project

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👨‍💻 Who Should Join?

এই কোর্সটি বিশেষভাবে উপযোগী—

• Students
• Python Developers
• Machine Learning Engineers
• Aspiring AI Engineers
• Data Scientists
• Researchers
• Software Engineers
• IT Professionals
• AI Enthusiasts
• Anyone interested in Deep Learning

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🎓 After Completing This Course

এই কোর্স শেষ করার পর আপনি পারবেন—

• Deep Learning-এর Core Concepts আত্মবিশ্বাসের সাথে বুঝতে।
• TensorFlow ও Keras ব্যবহার করে Neural Network তৈরি করতে।
• CNN ব্যবহার করে Image Classification Project তৈরি করতে।
• RNN ও LSTM ব্যবহার করে Sequential Data নিয়ে কাজ করতে।
• Deep Learning Models Train, Evaluate এবং Optimize করতে।
• Real-world AI Problems-এর জন্য Deep Learning Solutions তৈরি করতে।
• AI, Machine Learning ও Computer Vision-এর Advanced Learning-এর জন্য Strong Foundation তৈরি করতে।
• Industry-ready Deep Learning Skills অর্জন করতে।

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💼 Practical Projects

• Handwritten Digit Recognition
• Image Classification System
• Cat vs Dog Classifier
• Basic Face Mask Detection
• Sentiment Analysis Model
• Time Series Forecasting
• Transfer Learning Project
• Final End-to-End Deep Learning Capstone Project