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Course Features

Price

Original price was: £490.00.Current price is: £14.99.

Study Method

Online | Self-paced

Course Format

Reading Material - PDF, article

Duration

8 hours, 35 minutes

Qualification

No formal qualification

Certificate

At completion

Additional info

Coming soon

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Deep learning and NLP with Python course illustration showing AI brain, neural networks and language data visuals

Overview

Deep Learning and NLP with Python introduces you to one of the most in-demand skillsets in modern Artificial Intelligence. This course combines advanced deep learning fundamentals with practical natural language processing (NLP) techniques to help you design, train, and deploy intelligent systems. You’ll explore how neural networks learn patterns from data, apply dimensionality reduction with PCA, and build predictive models using TensorFlow and Keras.

Throughout the course, you’ll gain hands-on experience with essential algorithms such as multi-layer perceptrons, activation functions, and optimisers. You’ll also master real-world NLP applications, including spam detection, text classification, and sentiment analysis, using techniques like Bag of Words and TF-IDF vectorisation. With guided lessons and Python-based projects, you’ll learn how to preprocess data, visualise features, train models, and evaluate results confidently.

Whether you’re pursuing a career in AI or enhancing your data science skills, this course provides a practical path to mastering deep learning and natural language processing — two of the fastest-growing fields in technology today. By the end, you’ll be capable of building your own AI models that understand and interpret human language.

Upon completion, learners will receive a free digital course completion certificate.
Additionally, premium certificate and transcript options are available for purchase for professional or academic use. Students also enjoy 5-star rated support available 24/7 via email to ensure a smooth and successful learning experience.

This course is ideal for data analysts, Python developers, and aspiring AI engineers who want to apply deep learning and NLP techniques to real projects. It also suits students and professionals seeking a practical foundation in machine learning and AI-driven language technologies.
Basic knowledge of Python programming and an understanding of statistics or linear algebra will be helpful. No prior experience with deep learning or NLP is required, as all concepts are explained clearly with real-world coding examples.
Completing this course opens career opportunities in AI engineering, NLP research, data science, and machine learning development. Graduates can also advance to specialised roles like Deep Learning Engineer, NLP Developer, or AI Product Analyst — or pursue further academic study in artificial intelligence.

Who is this course for?

Deep Learning and NLP with Python introduces you to one of the most in-demand skillsets in modern Artificial Intelligence. This course combines advanced deep learning fundamentals with practical natural language processing (NLP) techniques to help you design, train, and deploy intelligent systems. You’ll explore how neural networks learn patterns from data, apply dimensionality reduction with PCA, and build predictive models using TensorFlow and Keras.

Throughout the course, you’ll gain hands-on experience with essential algorithms such as multi-layer perceptrons, activation functions, and optimisers. You’ll also master real-world NLP applications, including spam detection, text classification, and sentiment analysis, using techniques like Bag of Words and TF-IDF vectorisation. With guided lessons and Python-based projects, you’ll learn how to preprocess data, visualise features, train models, and evaluate results confidently.

Whether you’re pursuing a career in AI or enhancing your data science skills, this course provides a practical path to mastering deep learning and natural language processing — two of the fastest-growing fields in technology today. By the end, you’ll be capable of building your own AI models that understand and interpret human language.

Upon completion, learners will receive a free digital course completion certificate.
Additionally, premium certificate and transcript options are available for purchase for professional or academic use. Students also enjoy 5-star rated support available 24/7 via email to ensure a smooth and successful learning experience.

This course is ideal for data analysts, Python developers, and aspiring AI engineers who want to apply deep learning and NLP techniques to real projects. It also suits students and professionals seeking a practical foundation in machine learning and AI-driven language technologies.
Basic knowledge of Python programming and an understanding of statistics or linear algebra will be helpful. No prior experience with deep learning or NLP is required, as all concepts are explained clearly with real-world coding examples.
Completing this course opens career opportunities in AI engineering, NLP research, data science, and machine learning development. Graduates can also advance to specialised roles like Deep Learning Engineer, NLP Developer, or AI Product Analyst — or pursue further academic study in artificial intelligence.

Requirements

Deep Learning and NLP with Python introduces you to one of the most in-demand skillsets in modern Artificial Intelligence. This course combines advanced deep learning fundamentals with practical natural language processing (NLP) techniques to help you design, train, and deploy intelligent systems. You’ll explore how neural networks learn patterns from data, apply dimensionality reduction with PCA, and build predictive models using TensorFlow and Keras.

Throughout the course, you’ll gain hands-on experience with essential algorithms such as multi-layer perceptrons, activation functions, and optimisers. You’ll also master real-world NLP applications, including spam detection, text classification, and sentiment analysis, using techniques like Bag of Words and TF-IDF vectorisation. With guided lessons and Python-based projects, you’ll learn how to preprocess data, visualise features, train models, and evaluate results confidently.

Whether you’re pursuing a career in AI or enhancing your data science skills, this course provides a practical path to mastering deep learning and natural language processing — two of the fastest-growing fields in technology today. By the end, you’ll be capable of building your own AI models that understand and interpret human language.

Upon completion, learners will receive a free digital course completion certificate.
Additionally, premium certificate and transcript options are available for purchase for professional or academic use. Students also enjoy 5-star rated support available 24/7 via email to ensure a smooth and successful learning experience.

This course is ideal for data analysts, Python developers, and aspiring AI engineers who want to apply deep learning and NLP techniques to real projects. It also suits students and professionals seeking a practical foundation in machine learning and AI-driven language technologies.
Basic knowledge of Python programming and an understanding of statistics or linear algebra will be helpful. No prior experience with deep learning or NLP is required, as all concepts are explained clearly with real-world coding examples.
Completing this course opens career opportunities in AI engineering, NLP research, data science, and machine learning development. Graduates can also advance to specialised roles like Deep Learning Engineer, NLP Developer, or AI Product Analyst — or pursue further academic study in artificial intelligence.

Career path

Deep Learning and NLP with Python introduces you to one of the most in-demand skillsets in modern Artificial Intelligence. This course combines advanced deep learning fundamentals with practical natural language processing (NLP) techniques to help you design, train, and deploy intelligent systems. You’ll explore how neural networks learn patterns from data, apply dimensionality reduction with PCA, and build predictive models using TensorFlow and Keras.

Throughout the course, you’ll gain hands-on experience with essential algorithms such as multi-layer perceptrons, activation functions, and optimisers. You’ll also master real-world NLP applications, including spam detection, text classification, and sentiment analysis, using techniques like Bag of Words and TF-IDF vectorisation. With guided lessons and Python-based projects, you’ll learn how to preprocess data, visualise features, train models, and evaluate results confidently.

Whether you’re pursuing a career in AI or enhancing your data science skills, this course provides a practical path to mastering deep learning and natural language processing — two of the fastest-growing fields in technology today. By the end, you’ll be capable of building your own AI models that understand and interpret human language.

Upon completion, learners will receive a free digital course completion certificate.
Additionally, premium certificate and transcript options are available for purchase for professional or academic use. Students also enjoy 5-star rated support available 24/7 via email to ensure a smooth and successful learning experience.

This course is ideal for data analysts, Python developers, and aspiring AI engineers who want to apply deep learning and NLP techniques to real projects. It also suits students and professionals seeking a practical foundation in machine learning and AI-driven language technologies.
Basic knowledge of Python programming and an understanding of statistics or linear algebra will be helpful. No prior experience with deep learning or NLP is required, as all concepts are explained clearly with real-world coding examples.
Completing this course opens career opportunities in AI engineering, NLP research, data science, and machine learning development. Graduates can also advance to specialised roles like Deep Learning Engineer, NLP Developer, or AI Product Analyst — or pursue further academic study in artificial intelligence.

    • Introduction to Principal Component Analysis (PCA) 00:10:00
    • How PCA Works – Step-by-Step Breakdown 00:10:00
    • Loading and Understanding the MNIST Dataset 00:10:00
    • Real-World Applications of PCA 00:10:00
    • PCA Implementation in Python 00:10:00
    • PCA Compression and Explained Variance 00:10:00
    • Reconstructing Data from PCA Components 00:10:00
    • Choosing the Right Number of Components 00:10:00
    • PCA with 95% Information Retention 00:10:00
    • Comparing Model Accuracy With and Without PCA 00:10:00
    • What is an Artificial Neuron? 00:10:00
    • Introduction to Multi-Layer Perceptrons (MLP) 00:10:00
    • Shallow vs Deep Neural Networks 00:10:00
    • Activation Functions Explained 00:10:00
    • Understanding Backpropagation 00:10:00
    • Common Optimizers in Deep Learning 00:10:00
    • Step-by-Step Guide to Building a Neural Network 00:10:00
    • Installing TensorFlow on Windows 00:10:00
    • Installing TensorFlow on Linux 00:10:00
    • Loading the Customer Churn Dataset 00:10:00
    • Visualising Churn Data – Part 1 00:10:00
    • Visualising Churn Data – Part 2 00:10:00
    • Preprocessing Data for Deep Learning 00:10:00
    • Importing Keras Neural Network APIs 00:10:00
    • Getting Input Shape and Calculating Class Weights 00:10:00
    • Building the Deep Learning Model 00:10:00
    • Understanding the Model Summary 00:10:00
    • Training the Neural Network 00:10:00
    • Evaluating the Neural Network Model 00:10:00
    • Saving and Loading Deep Learning Models 00:10:00
    • Making Predictions on Real-Life Data 00:10:00
    • Introduction to Natural Language Processing (NLP) 00:10:00
    • Core NLP Techniques Overview 00:10:00
    • Popular NLP Tools and Libraries 00:10:00
    • Common Challenges in NLP 00:10:00
    • Bag of Words – Simple Text Embedding Technique 00:10:00
    • TF-IDF – Term Frequency-Inverse Document Frequency 00:10:00
    • Loading the Spam Detection Dataset 00:10:00
    • Preprocessing and Cleaning Text Data 00:10:00
    • Feature Engineering for Text Classification 00:10:00
    • Visualising Text Features with Pair Plots 00:10:00
    • Splitting Text Data into Train and Test Sets 00:10:00
    • Converting Text with TF-IDF Vectorisation 00:10:00
    • Evaluating NLP Models and Predicting Outcomes 00:10:00
    • Saving and Loading NLP Models 00:10:00
    • Exam of Deep Learning and NLP with Python 00:50:00
    • Premium Certificate 00:15:00
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Yes, our premium certificate and transcript are widely recognized and accepted by embassies worldwide, particularly by the UK embassy. This adds credibility to your qualification and enhances its value for professional and academic purposes.

Yes, this course is designed for learners of all levels, including beginners. The content is structured to provide step-by-step guidance, ensuring that even those with no prior experience can follow along and gain valuable knowledge.

Yes, professionals will also benefit from this course. It covers advanced concepts, practical applications, and industry insights that can help enhance existing skills and knowledge. Whether you are looking to refine your expertise or expand your qualifications, this course provides valuable learning.

No, you have lifetime access to the course. Once enrolled, you can revisit the materials at any time as long as the course remains available. Additionally, we regularly update our content to ensure it stays relevant and up to date.

I trust you’re in good health. Your free certificate can be located in the Achievement section. The option to purchase a CPD certificate is available but entirely optional, and you may choose to skip it. Please be aware that it’s crucial to click the “Complete” button to ensure the certificate is generated, as this process is entirely automated.

Yes, the course includes both assessments and assignments. Your final marks will be determined by a combination of 20% from assignments and 80% from assessments. These evaluations are designed to test your understanding and ensure you have grasped the key concepts effectively.

We are a recognized course provider with CPD, UKRLP, and AOHT membership. The logos of these accreditation bodies will be featured on your premium certificate and transcript, ensuring credibility and professional recognition.

Yes, you will receive a free digital certificate automatically once you complete the course. If you would like a premium CPD-accredited certificate, either in digital or physical format, you can upgrade for a small fee.

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Course Features

Price

Original price was: £490.00.Current price is: £14.99.

Study Method

Online | Self-paced

Course Format

Reading Material - PDF, article

Duration

8 hours, 35 minutes

Qualification

No formal qualification

Certificate

At completion

Additional info

Coming soon

  • Share

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