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Tutorial Series

Deep-dive into topics with our multi-part tutorial series

16 Series
78 Episodes
📚

Smart Factory with AI

AI/Deep Learning 12 episodes
  1. 1. Smart Factory Fundamentals: How AI Actually Works in Manufacturing
  2. 2. Computer Vision for Quality Control: Defect Detection Basics
  3. 3. Predictive Maintenance 101: Using Machine Learning to Prevent Downtime
  4. 4. Real-Time Anomaly Detection on Production Lines with Deep Learning
  5. 5. Digital Twin Technology: Creating Virtual Factory Replicas with Python
  6. 6. Reinforcement Learning for Production Scheduling: Why DQN Failed and How PPO Saved Our Factory Line
  7. 7. Edge AI vs Cloud AI: Choosing the Right Architecture for Factories
  8. 8. Time Series Forecasting for Demand Planning: Why Prophet Fails in Factories
  9. 9. Object Detection and Tracking: Monitoring Assembly Line Workflows
  10. 10. Sensor Fusion and IoT Integration in Smart Manufacturing
  11. 11. Explainable AI for Factory Operations: Building Trust in Automated Decisions
  12. 12. Building an End-to-End Smart Factory AI Pipeline: Case Study and Best Practices
📚

Quant Investment with Python

Data Analysis 8 episodes
  1. 1. Getting Started with Quantitative Investment in Python
  2. 2. Data Collection and Preprocessing for Quant Trading in Python
  3. 3. Technical Indicators and Feature Engineering with Pandas for Quant Trading
  4. 4. Backtesting Frameworks: Building Your First Trading Strategy
  5. 5. Risk Management and Portfolio Optimization Techniques in Python
  6. 6. Machine Learning Models for Stock Price Prediction: Why Most Fail and What Actually Works
  7. 7. Pairs Trading Is Dead (Unless You Know Where to Look)
  8. 8. Real-Time Trading Systems and Deployment Best Practices
🎯

RL Complete Guide

Reinforcement Learning 6 episodes
  1. 1. Part 1: The Core of RL: Markov Decision Processes (MDP) Explained
  2. 2. Part 2: Building Your First Custom Gym Environment using OpenAI Gymnasium
  3. 3. Part 3: Policy Gradient vs. Q-Learning: Choosing the Right Agent
  4. 4. Part 4: Stable Baselines3: Practical Tips for Training Robust Agents
  5. 5. Part 5: Reward Engineering: How to Shape Behaviors in Financial/Robotic Tasks
  6. 6. Part 6: Beyond Simulation: Addressing the Sim-to-Real Gap
📊

Kaggle Financial

Data Analysis 6 episodes
  1. 1. Navigating the Landscape of Financial Datasets on Kaggle
  2. 2. Exploratory Data Analysis (EDA) for Stock Price Prediction
  3. 3. Advanced Feature Engineering for Financial Time-Series
  4. 4. Building a Credit Risk Scoring Model with Machine Learning
  5. 5. Detecting Financial Fraud using Anomaly Detection Techniques
  6. 6. Deep Learning for Algorithmic Trading: From LSTM to Transformers
📚

US Stock Market Analyzer

Data Analysis 5 episodes
  1. 1. Building a US Stock Market Data Pipeline with Python and Yahoo Finance API
  2. 2. Plotly Defeats Matplotlib for Stock Visualization: Here's the Math
  3. 3. Sentiment Analysis on Financial News Using NLP for Stock Prediction
  4. 4. Building a Portfolio Optimization Engine with Modern Portfolio Theory in Python
  5. 5. Deploying a Real-Time Stock Market Dashboard with FastAPI and WebSockets
📚

Game AI with Reinforcement Learning

Reinforcement Learning 5 episodes
  1. 1. Game AI with Reinforcement Learning: Why RL Beats Traditional Methods
  2. 2. Q-Learning for Grid Worlds: Building Your First Game AI Agent
  3. 3. Deep Q-Networks (DQN): Training AI to Play Atari Games
  4. 4. Policy Gradient Methods: PPO and A3C for Complex Game Environments
  5. 5. Advanced Game AI: Multi-Agent RL, Curriculum Learning, and Self-Play
💹

Financial NLP

AI/Deep Learning 5 episodes
  1. 1. Part 1: Sentiment Analysis of Financial News using FinBERT
  2. 2. Part 2: Mapping Market Volatility to Global News Headlines
  3. 3. Part 3: Decoding Central Bank Speeches with NLP (Fed Meetings)
  4. 4. Part 4: Extracting Alpha Signals from Social Media (Twitter/X)
  5. 5. Part 5: Automating Earnings Call Summarization with LLMs
🥇

Gold Price Forecasting with Data Analysis and Deep Learning

Data Analysis 4 episodes
  1. 1. Gold Price Analysis: Pattern Recognition in 10 Years of Market Data
  2. 2. Classical vs Neural Time Series: ARIMA and LSTM Head-to-Head on Gold Prices
  3. 3. LSTM vs Transformer for Gold Price Forecasting: A Practical Showdown
  4. 4. Production-Ready Gold Price Prediction: From Jupyter Notebook to REST API
📊

Data Analysis Foundations

Data Analysis 4 episodes
  1. 1. Part 1: Beyond Static Charts: Building Interactive Dashboards with Plotly/Streamlit
  2. 2. Part 2: Statistical Rigor: Why Your Correlation Might Be Spurious
  3. 3. Part 3: Handling Imbalanced Data: SMOTE, ADASYN, and Beyond
  4. 4. Part 4: Explainable AI (XAI): Using SHAP and LIME to Interpret Complex Models
🎙️

Whisper and On-device AI Optimization

AI/Deep Learning 4 episodes
  1. 1. Optimizing Whisper for Mobile: Model Quantization and Compression Techniques
  2. 2. On-Device Inference: Running Whisper Efficiently with ONNX and Core ML
  3. 3. Real-time Whisper Is a Battery Nightmare (Here's How to Fix It)
  4. 4. Whisper Fundamentals: Understanding OpenAI's Speech Recognition Model Architecture
📚

CBM Portfolio Project

CBM/PHM 4 episodes
  1. 1. Building a Condition-Based Maintenance System from Scratch: Sensor Data Collection and Preprocessing
  2. 2. Feature Engineering for Predictive Maintenance: Extracting Health Indicators from Vibration and Temperature Data
  3. 3. Training and Evaluating RUL Prediction Models: From Classical ML to LSTM Networks
  4. 4. Deploying a Real-Time CBM Dashboard: End-to-End Pipeline with Alerts and Visualization
📉

Stock Price Data Analysis

Data Analysis 3 episodes
  1. 1. Stock Price Analysis Python: yfinance vs pandas-datareader in 2026
  2. 2. Technical Indicators and Trading Signals: Moving Averages, RSI, and MACD in Practice
  3. 3. Time Series Stock Forecasting: Why ARIMA Failed and LSTM Barely Worked
🔧

RUL Prediction

CBM/PHM 3 episodes
  1. 1. Introduction to PHM: What Is Remaining Useful Life (RUL) Prediction? From Concepts to Data Preparation
  2. 2. Building RUL Prediction Models in Python: Step-by-Step from Linear Regression to LSTM
  3. 3. Deploying RUL Prediction Models: Evaluation, Optimization, and Real-World PHM System Integration
🤖

Upbit Trading Bot

Python Tips 3 episodes
  1. 1. Building Your First Upbit Trading Bot: Setup and Authentication
  2. 2. Upbit Trading Bot Part 2: Market Analysis and Order Execution
  3. 3. Advanced Trading Bot Features: Risk Management and Backtesting
💻

Claude Code

DevTools & Productivity 3 episodes
  1. 1. Claude Code: Getting Started with AI-Powered Development in Your Terminal
  2. 2. Advanced Claude Code Techniques: Multi-Agent Workflows and Custom Skills
  3. 3. Building Production Systems with Claude Code: Best Practices and Real-World Automation
🐍

Python Decorators

Python Tips 3 episodes
  1. 1. Python Decorators for Beginners: Understanding @syntax and First-Class Functions
  2. 2. Writing Custom Python Decorators: Args, Returns, and Real-World Patterns
  3. 3. Advanced Python Decorator Techniques: Classes, Stacking, and Production Best Practices
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