Python Advanced Course

Python for Advanced Data Analysis & Machine Learning

Master advanced data science cores, from interactive dashboards to Deep Learning ANN.

This course is the advanced version of the Python Starter class, focusing on complex data models, interactive visualizations, and an introduction to Deep Learning.

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Course Introduction

Designed for students who already have a basic understanding of Python, this course dives deep into advanced applications of data science. We start with a recap of Pandas and Scikit-learn, then move on to building professional interactive dashboards with Dash. The course highlights multiple modern machine learning models (e.g., RandomForest, XGBoost) and introduces students to the field of Deep Learning, covering the basics of building Artificial Neural Networks with Keras.

Course Syllabus (Total 8 Hours)

Session 1: Pandas & Scikit-learn Recap + Advanced Cursor AI (2 Hours) • Quick recap of data processing and ML workflows • Advanced Cursor AI Prompting techniques and Agent mode usage • Case Study: Refactoring and optimizing existing data analysis code with AI
Session 2: Interactive Dashboards & Visualization Systems (2 Hours) • Building interactive dashboards by combining Pandas, Plotly, and Dash • Transforming static data into scalable, dynamically filterable visualization systems • Case Study: Creating a product sales KPI dashboard to track business trends in real-time
Session 3: Advanced Data Models & Scikit-learn Practice (2 Hours) • In-depth Pandas techniques for advanced data transformation • Intro to more models: Linear Regression, Logistic Regression, RandomForest, XGBoost, Isolation Forest • Case Study: Using multiple models for credit scoring prediction or anomaly detection
Session 4: Intro to Deep Learning: ANN & Keras (2 Hours) • Basic concepts and architecture of Artificial Neural Networks (ANN) • Basic usage of Keras framework and model training • Hands-on: Building your first simple neural network prediction model with Keras

Suitable for students who have completed the Python Starter course or have basic Python knowledge