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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.

Machine Learning is reshaping industries faster than you can say "algorithm". Our Machine Learning with Python Course is built for those who are genuinely curious about how machines learn, make decisions, and improve with data. With Python as your trusty companion, you’ll explore the key concepts and core techniques behind predictive modelling, supervised and unsupervised learning, and data-driven algorithms—all explained in a clear and digestible manner. No fluff, no filler—just solid learning with a structured approach. You’ll journey through essential modules that guide you from the fundamentals of machine learning to building models that actually do something meaningful. Whether you're brushing up your CV or aiming to understand how systems like recommendation engines or fraud detection work, this course offers insight that clicks. Python’s role in the process isn’t treated as a side note—it's woven through each section so you're building knowledge that’s both relevant and up-to-date in today’s data-focused world. If you’re ready to treat your brain to some serious logic and clever code, then this course has your name written in Pythonic syntax. Learning Outcomes: Understand the fundamentals of machine learning. Manipulate data using Numpy and Pandas libraries. Build and evaluate machine learning models using Sklearn pipeline and column transformer. Explore the world of data analysis with Pandas DataFrame. Contribute to the development of cutting-edge technology in the field of machine learning. The Machine Learning with Python course is designed to provide you with the skills and knowledge needed to develop and evaluate machine learning models using Python. In this course, you'll learn how to manipulate data using Numpy and Pandas libraries, build and evaluate machine learning models using Sklearn pipeline and column transformer, and explore the world of data analysis with Pandas DataFrame. The course is perfect for aspiring data scientists, machine learning engineers, and developers interested in machine learning development. By the end of this course, you'll have a deep understanding of the fundamentals of machine learning and how to contribute to the development of cutting-edge technology in this exciting field. With hands-on experience in manipulating data and building and evaluating machine learning models, you'll be well-equipped to start a career in machine learning. Machine Learning with Python Course Course Curriculum Section 01: Introduction Section 02: Numpy Library Section 03: Matplotlib Section 04: Polynomial Regression 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 machine learning development. Anyone interested in the field of machine learning. Professionals looking to upskill in the latest technology. Career path Aspiring data scientists. Machine learning engineers. Developers interested in machine learning development. Anyone interested in the field of machine learning. Professionals looking to upskill in the latest technology. 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.