163 Deep Learning courses

Master Deep Learning Heuristics with R! This course will teach you how to use Deep Learning Heuristics to solve complex problems in Agriculture, Cryptocurrencies, Energy Sector, and Financial Markets. With R, you will be able to develop and implement efficient and scalable solutions.

In this self-paced course, you will learn how to use TensorFlow 2 to build deep neural networks. You will learn the basics of machine learning, classification, and regression. We will also discuss the connection between artificial and biological neural networks and how that inspires our thinking in deep learning.

This comprehensive deep learning course with Python will start with the basics and work up to advanced topics such as using different frameworks in Python to solve real-world problems and building artificial neural networks with TensorFlow and Keras.

Get started with Neural networks and understand the underlying concepts of Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. This hands-on course will help you understand deep learning in detail with no prior coding or programming experience required.

This course equips learners with a comprehensive understanding of the NumPy stack, including NumPy, Matplotlib, Pandas, and SciPy, to effectively tackle common challenges in deep learning and data science. Master the basics with this carefully structured course.

In this course, you will be learning one of the widely used deep learning frameworks, that is, PyTorch, and learn the basics of convolutional neural networks in PyTorch. We will also cover the basics of Python and understand how to implement different Python libraries.

In this self-paced course, you will learn how to use TensorFlow 2 to build convolutional neural networks (CNNs). You will learn how to apply CNNs to several practical image recognition datasets and learn about techniques that help improve performance, such as batch normalization, data augmentation, and transfer learning.

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.

Stock markets move with more mystery than a magician’s deck of cards — but behind every dramatic rise and cryptic dip lies data, and data tells a story. This course dives straight into that narrative using deep learning techniques to forecast stock prices with logic, precision, and a pinch of technical finesse. Ideal for those ready to apply neural networks in finance-focused projects, the course simplifies complex theories without watering down their analytical power. From sequence modelling to time-series predictions using LSTM and beyond, you’ll explore how deep learning tools are being used to understand financial patterns and fluctuations. This course isn’t about abstract theory or vague strategies — it’s a focused look at how data science meets deep learning in the stock market sphere. Whether you’re a data enthusiast or an aspiring financial analyst, this course offers you the clarity and direction needed to interpret and anticipate stock price movement with greater confidence. 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. 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). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data scientists. Machine learning engineers. Developers interested in deep learning development. Anyone interested in the field of deep learning. Professionals looking to upskill in the latest technology. Career path Data Scientist: £40,000 to £80,000 per year. Machine Learning Engineer: £55,000 to £90,000 per year. Artificial Intelligence Developer: £40,000 to £80,000 per year. Quantitative Analyst: £30,000 to £80,000 per year. Financial Data Analyst: £25,000 to £60,000 per year. 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.

If you're fascinated by the mysteries of market movement and want to explore how machines attempt to predict tomorrow's numbers today, this Stock Price Prognostics Course will suit your curious streak perfectly. Built around deep learning models tailored for time series forecasting, the course takes a closer look at how algorithms can be trained to recognise patterns, spot trends, and occasionally raise an eyebrow at the randomness of stock data. It’s technical, structured, and surprisingly satisfying — no crystal ball involved, just code that tries its best. Focusing on stock price prognostics through real datasets, the course guides you through model building, evaluation metrics and common forecasting techniques using neural networks — all in plain English, with clear explanations and zero mystique. It’s suited to those who enjoy a challenge, appreciate a bit of data drama, and prefer graphs that actually say something. Whether you're brushing up on deep learning or building from the ground up, this course connects theory with application in a focused, jargon-light approach — and no need to wear a tie or trade a share. 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. ⊱⊱ 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 £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? Aspiring data scientists. Machine learning engineers. Developers interested in deep learning development. Anyone interested in the field of deep learning. Professionals looking to upskill in the latest technology. Career path Data Scientist: £40,000 to £80,000 per year. Machine Learning Engineer: £55,000 to £90,000 per year. Artificial Intelligence Developer: £40,000 to £80,000 per year. Quantitative Analyst: £30,000 to £80,000 per year. Financial Data Analyst: £25,000 to £60,000 per year. 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.