“This course was very helpful in gaining a broader idea of the concepts in AI (and used coding exercises to dive into the specifics)!”
Rachael
Welcome! 🌞
What to expect in this course 🤓
Let's get to know you📝
Chapter Introduction ⛷️
Recap of Fundementals 🛠️
FREE PREVIEWSine Function 〰️
Periodic Signals ⏰
Projection 📈
Wavelets 📉
How to use Google Colab for coding 💡
Coding Challenge 🚀
Quiz Activity - Transforming Signals 🧩
Chapter Survey - Transforming Signals 🌟
Chapter Introduction ⛷️
Introduction to Forecasting 🎯
FREE PREVIEWAuto Regressive Idea 💭
Auto Regressive Moving Average (ARMA) Model 👏
AIC Criterion 🤓
Coding Challenge 🚀
Quiz Activity - Time Series Forecasting 🧩
Chapter Survey - Time Series Forecasting 🌟
Chapter Introduction ⛷️
Supervised and Unsupervised Learning 🏷️
FREE PREVIEWK Means Clustering ✨
Dynamic Time Warping🧙♂️
Coding Challenge🚀
Quiz Actvity - Unsupervised Learning for Time Series 🧩
Chapter Survey - Unsupervised Learning for Time Series 🌟
Chapter Introduction⛷️
What is Deep Learning?🤔
FREE PREVIEWNeural Networks 🧠
Layers of Neural Networks🎂
Feed Forward Neural Network🔥
Last Steps📍
Coding Challenge🚀
Quiz Activity - Deep Learning and Time Series 🧩
Chapter Survey - Deep Learning and Time Series🌟
Extra Resources 😎
Congrats from us!🤩
Tell us about your experience 🙏
COURSE OVERVIEW
Learn about Deep Learning understand its basic principles.
Expand on Fourier Transform, Wavelet Transform and Chirplet Transform.
Use a Climate Time Series to forecast the weather with ARMA, SARMA and SARIMA models.
Learn about unsupervised learning and see how this can be applied to cluster different time series.
Use Deep Learning methods to denoise a Time Series and compress its information.
EMBRACE THE FUTURE OF DATA ANALYSIS
Neural networks are a powerful tool for predicting the next event in a signal.
For the first time, signal processing can use neural networks which learn from signal examples and make predictions even if they have no previous experience.
They have proven extremely useful, serving as a base for traditional signal processing and a revolutionary new tool for the next generation of signal processing applications.
Yes, you can! However, we recommend you start with the ‘Introduction to AI and Signal Processing Course’ as it will give you all the skills you need to conquer the intermediate course.
You should have a basic understanding of AI and Machine Learning. It will help to have some familiarity with Python, Google Colab and how to use Python Libraries.
Computer with an Internet connection, and access to a Google account.
Learn the basics about signals and statistics, and how to analyse, optimise and process signal data using Python for Machine Learning. Understand AI principles and ethics.
£24.99
Learn the basics about images, data compression, classification and colour detection using Python for Machine Learning. Understand AI principles and ethics.
£24.99
Apply advanced techniques to an image and perform real-world applications like image classification and image filtering using deep learning techniques.
£24.99
