Mastering Neural Networks & DL: Business Applications 2023

Section 01: Fundamentals of Neural Networks
Lecture 1: Introduction to Artificial Neural Networks
Lecture 2: Neuron Structure and Activation Functions
Lecture 3: Feedforward and Backpropagation
Lecture 4: Gradient Descent in NNs
Lecture 5: Applications of Neural Networks in Business

Section 02: Understanding Deep Learning
Lecture 6: Deep Learning vs. Traditional Machine Learning
Lecture 7: Deep Neural Networks Architecture
Lecture 8: Convolutional Neural Networks
Lecture 9: Recurrent Neural Networks
Lecture 10: Deep Learning Applications in Industry

Section 03: Neural Network Training Techniques
Lecture 11: Optimizing Neural Network Performance
Lecture 12: Regularization and Dropout
Lecture 13: Hyperparameter Tuning
Lecture 14: Transfer Learning
Lecture 15: Fine-Tuning Neural Networks for Business Scenarios

Section 04: Deep Learning for Image Recognition
Lecture 16: Image Data Preprocessing
Lecture 17: Convolutional Neural Networks for Images
Lecture 18: Object Detection with CNNs
Lecture 19: Deep Learning for Image Classification
Lecture 20: Real-Life Image Recognition Case Studies

Section 05: Natural Language Processing with Neural Networks
Lecture 21: Text Preprocessing for NLP
Lecture 22: Recurrent Neural Networks for Text Data
Lecture 23: Word Embeddings and LSTM
Lecture 24: Sentiment Analysis using RNNs
Lecture 25: NLP Applications in Business Communication

Section 06: Generative Adversarial Networks (GANs)
Lecture 26: Introduction to GANs
Lecture 27: GAN Architecture and Training Process
Lecture 28: Applications of GANs in Image Generation
Lecture 29: Challenges and Ethical Considerations of GANs
Lecture 30: Examples of GANs in Creative Industries

Section 07: Time Series Forecasting with RNNs
Lecture 31: Introduction to Time Series Data Analysis
Lecture 32: Recurrent Neural Networks for Time Series
Lecture 33: Long Short-Term Memory Networks
Lecture 34: Predictive Analytics with RNNs
Lecture 35: Time Series Forecasting in Business Contexts

Section 08: Anomaly Detection with Autoencoders
Lecture 36: Understanding Anomalies in Data
Lecture 37: Autoencoder Architecture
Lecture 38: Denoising Autoencoders
Lecture 39: Applications of Anomaly Detection in Fraud
Lecture 40: Real-Time Anomaly Detection Use Cases

Section 09: Reinforcement Learning Fundamentals
Lecture 41: Reinforcement Learning Basics
Lecture 42: Q-Learning and Markov Decision Processes
Lecture 43: Deep Q Networks (DQN)
Lecture 44: Policy Gradient Methods
Lecture 45: Reinforcement Learning in Game Theory

Section 10: Neural Networks for Customer Segmentation
Lecture 46: Segmentation Methods in Marketing
Lecture 47: Neural Network Clustering Techniques
Lecture 48: Targeted Marketing Campaigns
Lecture 49: Customer Lifetime Value Prediction
Lecture 50: Case Studies on Neural Segmentation in Business

Section 11: Sentiment Analysis in Social Media
Lecture 51: Social Media Data and Sentiment Analysis
Lecture 52: Deep Learning for Sentiment Detection
Lecture 53: Engagement Prediction with Sentiment Analysis
Lecture 54: Brand Reputation Monitoring
Lecture 55: Sentiment Analysis in Influencer Marketing

Section 12: Deep Learning for Business Optimization
Lecture 56: Optimizing Business Processes with DL
Lecture 57: Automating Decision-Making
Lecture 58: Dynamic Pricing Strategies
Lecture 59: Supply Chain Optimization
Lecture 60: DL in Inventory Management

Section 13: Neural Networks for Financial Forecasting
Lecture 61: Predictive Analytics in Finance
Lecture 62: Stock Price Prediction with NNs
Lecture 63: Risk Management in Banking
Lecture 64: Credit Scoring using Neural Networks
Lecture 65: Applications of NNs in Financial Sector

Section 14: Fraud Detection using Deep Learning
Lecture 66: Fraud Detection Techniques
Lecture 67: Deep Learning Models for Fraud
Lecture 68: Behavior-based Fraud Detection
Lecture 69: Anti-Money Laundering with DL
Lecture 70: Case Studies in Fraud Detection

Section 15: Business Strategy with Deep Learning Insights
Lecture 71: DL for Competitive Analysis
Lecture 72: Predictive Marketing Strategies
Lecture 73: Market Segmentation with NNs
Lecture 74: Strategic Decision Support Systems
Lecture 75: Deep Learning for Disruption Forecasting

Section 16: Neural Networks in Healthcare Management
Lecture 76: Medical Image Analysis with NNs
Lecture 77: DL for Disease Diagnosis
Lecture 78: Healthcare Data Security with Deep Learning
Lecture 79: Treatment Outcome Prediction
Lecture 80: Real-World Healthcare Applications of NNs

Section 17: Deep Learning for HR Management
Lecture 81: Talent Recruitment with Neural Networks
Lecture 82: Employee Performance Prediction
Lecture 83: Retention Strategies using Deep Learning
Lecture 84: Skills Gap Analysis
Lecture 85: HR Decision Support Systems

Section 18: Neural Networks for Supply Chain Optimization
Lecture 86: Forecasting Demand in Supply Chains
Lecture 87: Inventory Management with NNs
Lecture 88: Predictive Maintenance in Logistics
Lecture 89: Route Optimization using Neural Networks
Lecture 90: Applications of NNs in Supply Chain Efficiency

Section 19: Customer Personalization with Neural Networks
Lecture 91: Personalized Recommendations
Lecture 92: Segment-Specific Campaigns
Lecture 93: Customer Lifetime Value Prediction
Lecture 94: Neural Networks in Customer Retention
Lecture 95: Case Studies on Personalization Success

Section 20: Implementing Deep Learning Strategies
Lecture 96: Integration of Neural Networks in Business
Lecture 97: Data Privacy and Ethical Considerations
Lecture 98: Change Management in DL Adoption
Lecture 99: Organizational Culture Shifts
Lecture 100: Future Trends and Opportunities in DL Implementation