Description

Are you ready to unlock the full potential of convolutional neural networks and build your own deep learning projects? Do you want to take your skills to the next level and learn how to create advanced models for image recognition? If so, our Deep Learning Projects - Convolutional Neural Network course is perfect for you.

In this course, you'll learn everything you need to know to create your own convolutional neural network models for advanced image recognition tasks. From installing the necessary packages to data preprocessing and augmentation, you'll learn how to use Python to build advanced deep learning projects. You'll also gain a deeper understanding of data generators, different models, and how to evaluate the accuracy of your models.

So if you're ready to dive into the world of deep learning and take your skills to the next level, enrol in our Deep Learning Projects course today and start building your own convolutional neural network models.

Learning Outcomes:

Gain a solid understanding of convolutional neural networks and their applications in deep learning.

Learn how to install the necessary packages and set up a dataset structure for deep learning projects.

Discover how to create your own convolutional neural network model and layers using Python.

Understand how to preprocess and augment data for advanced image recognition tasks.

Learn how to evaluate the accuracy of your models and understand the different models available for deep learning projects.

The Deep Learning Projects - Convolutional Neural Network course is designed to provide you with the skills and knowledge you need to build your own advanced deep learning projects. Using Python, you'll learn how to install the necessary packages, set up a dataset structure, and create your own convolutional neural network model and layers. You'll also learn how to preprocess and augment data to enhance the accuracy of your models and evaluate the performance of your models using data generators.

â±â± Deep Learning Projects - Convolutional Neural Network Course Curriculum

Section 01: Introduction

Section 02: Installations

Section 03: Getting Started

Section 04: Accuracy

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).

CPD

10 CPD hours / points Accredited by CPD Quality Standards

Who is this course for?

Data analysts who want to expand their skills in deep learning and convolutional neural networks.

Programmers who want to learn how to build advanced models for image recognition.

Entrepreneurs who want to develop their own deep learning-based applications for image recognition.

Students who want to enhance their skills in deep learning and prepare for a career in the field.

Anyone who wants to explore the world of convolutional neural networks and deep learning projects.

Career path

Data Analyst: £24,000 - £45,000

Machine Learning Engineer: £28,000 - £65,000

Computer Vision Engineer: £30,000 - £70,000

Technical Lead: £40,000 - £90,000

Chief Technology Officer: £90,000 - £250,000

Certificates

Certificate of completion

Digital certificate - £9

You can apply for a CPD Accredited PDF Certificate at the cost of £9.

Certificate of completion

Hard copy certificate - £15

Hard copy can be sent to you via post at the expense of £15.

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Deep Learning Projects - Convolutional Neural Network Course

By One Education

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