161 Deep Learning courses

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Master Data Science skills using Python and real time project and go from Beginner to Super Advance level

Level 3 & 5 Endorsed Diploma | QLS Hard Copy Certificate Included | Plus 5 CPD Courses | Lifetime Access

The goal of this course is to use Python machine learning to create algorithms that you can use in the real world. You'll start with the basics of machine learning. You'll learn how to create, train, and optimize models and use these models in real-world applications.

Artificial Intelligence isn’t science fiction anymore — it’s shaping the way we search, shop, scroll, and sometimes even spill the tea. This course lays the groundwork for understanding how AI actually works — minus the jargon and dramatic movie scenes. You’ll explore essential concepts such as algorithms, data patterns, logic systems, and machine-based learning models, all presented in a format that makes sense even if your only prior experience with AI is arguing with your phone's voice assistant. Perfect for curious minds across industries, this foundational course covers the key principles that drive AI technologies, from basic neural networks to the role of big data in decision-making. Whether you're brushing up for academic reasons or looking to speak AI without sounding like a tech cliché, you’ll find this course insightful, neatly organised, and refreshingly down-to-earth. All content is delivered online, allowing you to study at your own pace — no awkward group projects or lab goggles required. Key Features CPD Accredited FREE PDF + Hardcopy certificate Fully online, interactive course Self-paced learning and laptop, tablet and smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Course Curriculum Module 01 : Introduction to Artificial Intelligence Module 02 : Mathematics for AI Module 03 : Knowledge Representation in AI - Part 1 Module 04 : Knowledge Representation in AI - Part 2 Module 05 : Machine Learning - Part 1 Module 06 : Machine Learning - Part 2 Module 07 : Deep Learning Module 08 : Natural Language Processing Module 09 : Computer Vision Module 10 : Robotics Module 11 : Building AI Applications Learning Outcomes: Grasp the fundamentals of artificial intelligence and its applications. Develop a strong mathematical foundation for AI algorithms. Master knowledge representation techniques in AI. Explore the principles and applications of machine learning. Dive into the world of deep learning and its use in AI. Understand the core concepts of natural language processing and computer vision. Accreditation This course is CPD Quality Standards (CPD QS) accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Technology enthusiasts eager to delve into AI. Students pursuing a career in AI and machine learning. Professionals seeking to upskill in the AI domain. Engineers and programmers interested in AI development. Entrepreneurs exploring AI for business solutions. Anyone with a curiosity about the future of artificial intelligence. Graduates looking to enhance their tech-related knowledge. Innovators with an interest in robotics and AI applications. Career path AI Research Scientist Machine Learning Engineer Data Scientist Natural Language Processing Engineer Computer Vision Specialist Robotics Software Engineer Certificates Digital certificate Digital certificate - Included Once you've successfully completed your course, you will immediately be sent a FREE digital certificate. Hard copy certificate Hard copy certificate - Included Also, you can have your FREE printed certificate delivered by post (shipping cost £3.99 in the UK). For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only £10. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Foundations of Artificial Intelligence Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Foundations of Artificial Intelligence Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Foundations of Artificial Intelligence Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Foundations of Artificial Intelligence Course, like every one of Skillwise's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Foundations of Artificial Intelligence? Unlimited access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD Quality Standard-accredited qualifications after course completion Receive one-to-one assistance every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Foundations of Artificial Intelligence there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Foundations of Artificial Intelligence course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skills. Prerequisites This Foundations of Artificial Intelligence does not require you to have any prior qualifications or experience. You can just enroll and start learning. This Foundations of Artificial Intelligence was made by professionals and it is compatible with all PCs, Macs, tablets, and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as a bonus, you will be able to pursue multiple occupations. This Foundations of Artificial Intelligence is a great way for you to gain multiple skills from the comfort of your home.   Module 1 Introduction to Artificial Intelligence Introduction to Artificial Intelligence 00:21:00 Module 2 Mathematics for AI Mathematics for AI 00:17:00 Module 3 Knowledge Representation in AI - Part 1 Knowledge Representation in AI - Part 1 00:18:00 Module 4 Knowledge Representation in AI - Part 2 Knowledge Representation in AI - Part 2 00:16:00 Module 5 Machine Learning - Part 1 Machine Learning - Part 1 00:16:00 Module 6 Machine Learning - Part 2 Machine Learning - Part 2 00:15:00 Module 7 Deep Learning Deep Learning 00:16:00 Module 8 Natural Language Processing Natural Language Processing 00:22:00 Module 9 Computer Vision Computer Vision 00:14:00 Module 10 Robotics Robotics 00:18:00 Module 11 Building AI Applications Building AI Applications 00:24:00

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | Plus 10 CPD Courses | Lifetime Access

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

Are you intrigued by how speech recognition is driving the growth of the AI market? This course is a reliable guide if you're looking to pursue a career as a speech recognition professional and understand industry best practices.

The course is crafted to reflect the in-demand skills in the marketplace that will help you in mastering the key concepts and methodologies of RL and deep RL, along with several practical implementations. This course will help you know the theory and practical aspects of reinforcement and deep reinforcement learning.