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Hands on Deep Learning Projects - Stock price Prognostics Course

Booking options

£12

Highlights

On-Demand course
2 hours
All levels

Description

The Hands on Deep Learning Projects – Stock Price Prognostics Course explores how deep learning models are applied to stock price prognostics using structured datasets and algorithmic methods. This course focuses on neural networks, historical market data interpretation, and model-driven forecasting techniques used in financial analysis. Learners are introduced to key deep learning concepts relevant to stock price movements, including data preparation, feature selection, and evaluation metrics, all explained in a clear and approachable manner.

The course places strong emphasis on analytical thinking and model behaviour rather than surface-level predictions. Attention is given to understanding trends, volatility, and patterns within financial time series using deep learning frameworks. Concepts are presented in a logical sequence, supporting gradual knowledge development without unnecessary complexity. Designed for those interested in data-driven financial insights, this course supports professional development by strengthening understanding of how deep learning supports stock price prognostics in modern financial contexts.

Learning Outcomes:

Build a deep learning model using RNN that can accurately predict stock prices.

Preprocess data and perform exploratory data analysis.

Scale features and make predictions on test data.

Gain real-world experience in deep learning development.

Contribute to the development of cutting-edge technology in the finance industry.

The Hands-on Deep Learning Projects - Stock Price Prognostics course is designed to provide you with the skills and knowledge needed to develop a deep learning model using RNN that can accurately predict stock prices. In this course, you'll learn how to preprocess data, perform exploratory data analysis, scale features, and make predictions on test data. The course is perfect for aspiring data scientists, machine learning engineers, and developers interested in deep learning development.

By the end of this course, you'll have a deep understanding of how to build a deep learning model that can revolutionise the world of finance. With hands-on experience in developing cutting-edge technology, you'll be well-equipped to start a career in deep learning and contribute to the development of cutting-edge technology in the finance industry.

â±â± Hands on Deep Learning Projects - Stock price Prognostics Course Curriculum

Section 01: Introduction

Section 02: Installation of Tools and Libraries

Section 03: Dataset

Section 04: EDA

Section 05: Feature Scaling

Section 06: Building RNN

Section 07: Prediction on Test Data

Section 08: Output

How is the course assessed?

Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%.

Exam & Retakes:
It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.

Certification
Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).