Description
Overview:
Welcome to “Project on Deep Learning – Artificial Neural Network”! This course is designed to provide hands-on experience in building and training artificial neural networks (ANNs) for deep learning projects. ANNs are a fundamental component of deep learning, enabling the modeling of complex patterns and relationships in data. In this course, you’ll learn how to design, implement, and optimize ANNs for various applications, empowering you to tackle real-world problems using deep learning techniques.
Interactive video lectures by industry experts
Instant e-certificate and hard copy dispatch by next working day
Fully online, interactive course with Professional voice-over
Developed by qualified first aid professionals
Self paced learning and laptop, tablet, smartphone friendly
24/7 Learning Assistance
Discounts on bulk purchases
Main Course Features:
Comprehensive coverage of artificial neural network architecture and principles
Practical projects and exercises to reinforce learning and understanding
Implementation of deep learning frameworks such as TensorFlow or PyTorch
Exploration of advanced neural network architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs)
Guidance on data preprocessing, model training, and evaluation techniques for ANNs
Real-world case studies and examples showcasing the applications of artificial neural networks
Access to resources and tools for building and testing deep learning models
Supportive online community for collaboration and assistance throughout the course
Who Should Take This Course:
Data scientists and machine learning enthusiasts interested in diving deep into deep learning techniques
Developers and programmers seeking to expand their skill set to include artificial neural networks for solving complex problems
Students and professionals aiming to pursue a career in artificial intelligence and deep learning research or development
Learning Outcomes:
Understand the fundamentals of artificial neural networks and deep learning
Design and implement artificial neural network architectures for various applications
Apply deep learning techniques to solve real-world problems and challenges
Train and optimize neural network models for improved performance and accuracy
Explore advanced neural network architectures such as CNNs and RNNs
Evaluate and interpret the performance of deep learning models
Develop a portfolio of deep learning projects showcasing proficiency in artificial neural networks
Stay updated with the latest advancements and trends in deep learning and artificial intelligence.
Certification
Once you’ve successfully completed your course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99). All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.
Assessment
At the end of the Course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.
Curriculum
Section 01: Introduction
Section 02: ANN Installation
Section 03: Data Preprocessing
Section 04: Data Encoding
Section 05: Steps to Build ANN
Section 06: Predictions and Imbalance-Learn
