Course curriculum

    1. 1. Business Context

    2. Materials

    3. 2.Features Required

    4. 3. Data Architecture Model

    5. 4. Data Source Structure Discovery

    6. 5. DWH DB Creation

    7. 6. Apache Nifi - DWH Loading

    8. 7. Notebook: Import libraries, Data, EDA and visualizations

    9. 8. Random Forest Algorithm

    10. 9. Notebook: Feature engineering, Train, Test Data & Predict New customerData

    11. 10. Notebook: Predict New Customer Data (cont.)

    12. 11. XGBoost Algorithm

    13. 12. Notebook: XGBoost Modelling & Hyperparameter Optimization

    14. 13. Collaborative Filtering Algorithm with Cosine Similarity

    15. 14. Notebook: Item-Based Collaborative Filtering

    16. 15. Notebook: Extend Item-Based Collaborative Filtering

    1. 1. MySQL Installation

    2. 2. Apache Nifi Installation

    3. 3. Anaconda & Python Installation and Configuration

    1. Special Gift For You (Bonus)

About this course

  • $24.00
  • 20 lessons
  • 2.5 hours of video content

Product Recommendation – Personalized Credit Card Recommendations in Banking

🎓 What You'll Learn:

  • 🔍 Understand the fundamentals of personalized credit card recommendations in banking.
  • 📊 Build data-driven models to optimize approval probability and credit limits.
  • 💳 Match customers to the perfect credit card based on profiles and spending habits.
  • 🏆 Align reward types with customer preferences for higher engagement and loyalty.
  • 🤖 Use Apache NiFi, MySQL, and machine learning (Random Forest, XGBoost) for real-world applications.

🛠 Requirements:

  • 💻 Basic knowledge of SQL and Python.
  • 🧠 Familiarity with machine learning concepts is beneficial but not required.
  • 🌐 Interest in banking, finance, and data science applications.

📘 Description:

In this course, you'll explore the power of personalized credit card recommendations to enhance customer satisfaction and loyalty in banking. From learning how to predict approval likelihood to aligning rewards with spending habits, gain hands-on experience with tools like Apache NiFi, MySQL, and machine learning techniques. Perfect for data enthusiasts and banking professionals who want to take customer insights to the next level!

👥 Who This Course is For:

  • 📊 Data scientists and analysts eager to work with financial data.
  • 💼 Banking and finance professionals looking to improve product offerings.
  • 🧑‍💻 Students or professionals interested in machine learning applications.
  • 🚀 Anyone passionate about fintech and personalized customer experiences.

Discover your potential, starting today

Enroll today