Hands on Deep Learning Projects - Stock price Prognostics

Hands on Deep Learning Projects – Stock Price Prognostics is a practical, project-based course that teaches you how to build a deep learning model for stock price prediction using real financial data. Combining artificial intelligence, neural networks, and time series forecasting, you’ll gain hands-on experience developing a real-world AI project from data preparation to model evaluation.

You’ll learn how to collect, clean, and prepare stock market data, apply data scaling techniques, and build a Recurrent Neural Network (RNN) to forecast future stock prices. The course also covers model training, performance evaluation, and data visualisation, helping you understand how deep learning models make predictions and interpret their results.

Whether you’re interested in deep learning with Python, machine learning, financial forecasting, data science, or AI applications in finance, this course provides practical experience while helping you build an impressive portfolio project. No advanced experience requires just curiosity and a willingness to learn by building real-world solutions.

Learning Outcomes

• Set up the tools and libraries needed for a deep learning project
• Explore and prepare real stock market data ready for modelling
• Apply feature scaling to improve how accurately a model performs
• Build and train a recurrent neural network suited to time-based data
• Test a trained model’s predictions against real, unseen data
• Visualise results clearly to show how well a model has performed
• Complete a full, practical project applying deep learning to real financial data