The Artificial Intelligence Course in London, developed in partnership with IBM, is a leading-edge certification for professionals wanting to advance in the domain. By completing this AI Course in London, you will have gained work-ready expertise in the fundamentals including Data Science using Python, Natural Language Processing, Machine and Deep Learning, and more taught by leading experts via live online classes, and masterclasses from industry experts.
Earn a program certificate and up to 22 CEU credits from Caltech CTME
Obtain industry-recognized IBM certificates for IBM courses and get access to masterclasses by IBM
Earn a membership to Caltech CTME circle and an online convocation by the Caltech program director.
Attend live online classes on generative AI, prompt engineering, explainable AI, ChatGPT, and more
Our Artificial Intelligence course comes with Simplilearn’s Career Assistance service that has demonstrated strong performance by means of average salaries offered, the number of hiring companies participating, and the pace of job offer roll-outs.
Maximum salary hike150%
Average salary hike70%
Designed and perfected to boost your career as an AI and ML professional, this Artificial Intelligence Course in London showcases Caltech CTMEs excellence and IBM's industry prowess. The AI courses in London cover key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.
Our extensive program empowers you to thrive in your career by providing essential skills and knowledge. Through a well-structured learning approach and industry-relevant projects, you'll tackle complex challenges to remain at the forefront.
Unlock your potential as an Artificial Intelligence and Machine Learning professional with industry-relevant AI courses. In this Artificial Intelligence course, you will learn about various AI-based technologies.
Welcome to this Artificial Intelligence Course, developed and presented with Caltech CTME and IBM, which will help you become an AI & ML domain expert.
The Mathematics and Statistics Foundations course establishes a strong mathematical and statistical principles base, fostering critical thinking and problem-solving skills. This course equips students with the ability to analyze data, make informed decisions, and apply these techniques to relevant industry scenarios. It serves as an essential starting point for further learning in the program.
This course provides you with essential Python programming skills that will serve as the building blocks for your entire program journey. You will learn how to effectively implement artificial intelligence (AI) and machine learning (ML) algorithms, conduct data analysis, and construct intelligent systems efficiently using Python
Developed by IBM, this course equips students with the skills to leverage Python for data science. By the end of the course, participants will be proficient in writing Python scripts and performing hands-on data analysis using a Jupyter-based lab environment.
This course provides coverage of key concepts in data science, such as data preparation, model development, and evaluation. Throughout the course, you will develop a strong understanding of fundamental Python concepts such as strings, Lambda functions, and lists. You will explore various important skills such as Z-test, T-test, and ANOVA. Furthermore, you will acquire data visualization skills using popular libraries like Matplotlib, Seaborn, Plotly, and Bokeh.
This course comprehensively covers various types of machine learning and their practical applications. You will explore the machine learning pipeline and delve into topics such as supervised learning, regression models, and classification algorithms. You will also study unsupervised learning, including clustering techniques and ensemble modeling. Evaluate machine learning frameworks like TensorFlow and Keras, and build a recommendation engine with PyTorch.
Elevate your machine learning skills to the next level with this comprehensive course on deep learning using TensorFlow and Keras. Gain a thorough understanding of deep learning concepts, empowering you to construct artificial neural networks and navigate through complex data abstraction layers. By harnessing the potential of data, this course prepares you to venture into new frontiers of Artificial Intelligence.
This comprehensive course provides you with the necessary skills to deploy deep learning tools using AI/ML frameworks. You will explore the fundamental concepts and applications of deep learning and understand the distinctions between DL and ML. The course covers a range of topics, including neural networks, forward and backward propagation, TensorFlow 2, Keras, model interpretability, CNNs, transfer learning, object detection,RNNs, autoencoders, and creating neural networks in PyTorch.
This comprehensive course thoroughly explains generative AI models, specifically focusing on ChatGPT. Participants will acquire practical skills to leverage ChatGPT for building and deploying AI chatbot applications effectively. The course covers topics such as generative AI, explainable AI, prompt engineering, fine-tuning, ethical considerations, and the future of generative AI.
The capstone project allows you to implement the skills you learned throughout this bootcamp. You will solve industry-specific challenges by leveraging various AI and ML techniques. The capstone project is the final step in the core learning path and will help you showcase your expertise to employers.
Attend an online interactive masterclass and get insights about advancements in technology/techniques in AI and Machine Learning by Caltech
Attend this online interactive industry master class to gain insights about advancements in AI and Machine Learning techniques
In this advanced course, you will gain in-depth knowledge and practical skills in computer vision and deep learning techniques. The course covers various topics, including image formation and processing, convolutional neural networks (CNNs), object detection, image segmentation, generative models, optical character recognition, distributed and parallel computing, explainable AI (XAI), and deploying deep learning models.
This advanced course comprehensively explores applying machine learning algorithms to process vast amounts of natural language data. It focuses primarily on natural language understanding, feature engineering, natural language generation, automated speech recognition, speech-to-text conversion, text-to-speech conversion, voice assistance devices, and building Alexa skills.
This course delves into the core concepts of reinforcement learning (RL), providing you with the knowledge and skills to solve RL problems using various strategies in Python and TensorFlow. You will learn the theoretical foundations of RL and gain practical experience in applying RL algorithms as a problem-solving strategy. By the end of the course, you will be equipped with the skills to use reinforcement learning in diverse applications and scenarios effectively.
( Toll Free )
Develop a shopping app for an e-commerce company using Python
Using data science techniques, such as time series forecasting, to help a data analytics company forecast demand for different restaurant items.
Use exploratory data analysis and statistical techniques to understand the factors contributing to a retail firm's customer acquisition.
Perform feature analysis to understand the features of water bottles using EDA and statistical techniques to understand their overall quality and sustainability.
Use feature engineering to identify the top factors that influence price negotiations in the homebuying process.
Perform cluster analysis to create a recommended playlist of songs for users based on their user behavior.
Build a machine learning model that predicts employee attrition rate at a company by identifying patterns in their work habits and desires to stay with the company.
Use deep learning concepts, such as CNN, to automate a system that detects and prevents faulty situations resulting from human error.
Use deep learning to construct a model that predicts potential loan defaulters and ensures secure and trustworthy lending opportunities for a financial institution.
Use distributed training to construct a CNN model capable of detecting diabetic retinopathy and deploy it using TensorFlow Serving for an accurate diagnosis.
Leverage deep learning algorithms to develop a facial recognition feature that helps diagnose patients for genetic disorders and their variations.
Examine accident data involving Tesla’s auto-pilot feature to assess the correlation between road safety and the use of auto-pilot technology.
Use AI to categorize images of historical structures and conduct EDA to build a recommendation engine that improves marketing initiatives for historic locations.
Disclaimer - The projects have been built leveraging real publicly available data-sets of the mentioned organizations.
Dr. Rick Hefner serves as the Program Director for Caltech’s CTME, where he develops customized training programs for technology-driven organizations. He has over 40 years of experience in systems development and has served in academic, industrial, and research positions.
Artificial Intelligence is the next digital frontier, with profound implications for business and society. With the AI market expected to grow steadily over the years, this Artificial Intelligence course is perfect for those who want to stay ahead of the trend!
Expected global AI market value by 2027
Projected CAGR of the global AI market from 2023-2030
Expected total contribution of AI to the global economy by 2030
This PGP AI Course caters to working professionals from a variety of industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.
The AI Course application process consists of three steps. An offer of admission will be made to the selected candidates and accepted by the candidates by paying the admission fee.
Tell us a bit about yourself and why you want to do this AI Course
An admission panel will shortlist candidates based on their application
Selected candidates can begin the AI Course online within 1-2 weeks
For admission to this Artificial Intelligence Course, candidates should have:
Our Artificial Intelligence course offers Caltech CTME's excellence and IBM's industry prowess to help you get ahead of the curve. The admission fee for this PGP AI ML is £ 3,990
We are dedicated to making our programs accessible. We are committed to helping you find a way to budget for this program and offer a variety of financing options to make it more economical.
2 Oct, 2023
25 Nov, 2023 - 24 Nov, 2024
03:30 - 07:30 GMT
Weekend (Sat - Sun)
4 Oct, 2023
21 Oct, 2023 - 27 Oct, 2024
14:30 - 18:30 BST
Weekend (Sat - Sun)
For admission to this AI course in London, candidates should have:
A bachelor's degree with an average score of at least 50 percent
Prior knowledge or experience in programming and mathematics
2+ years of formal work experience (preferred)
Professionals eager to develop AI and ML expertise with the objective of:
Enhancing effectiveness in their current role
Transitioning to AI roles in their organization
Seeking to advance their career in the industry
Giving shape to entrepreneurial aspirations
The admission process for this AI Course in London consists of three simple steps:
All interested candidates are required to apply through the online application form
An admission panel will shortlist the candidates based on their application
An offer of admission will be made to the selected candidates, which can then be accepted by the candidate by paying the AI Course fee
To ensure money is not a barrier in the path of learning, we offer various financing options to help ensure that this AI course in London is financially manageable. Please refer to our “Admissions Fee and Financing” section for more details.
As a part of this AI Course in London you will receive the following:
Upon successful completion of this AI course in London, you will be awarded a certificate of completion by Caltech CTME, along with IBM certificates for IBM courses, and industry-recognized certification from Simplilearn for courses in the learning path.
Once you make the first installment of the fee for this Artificial Intelligence Course in London, you also will get access to a preparatory course. You will have to go through the assigned course before starting the first class, which consists of self-paced learning content in the form of videos.
The AI course in London could be completed according to your schedule but the anticipated time to complete the overall course is 6-8 months
This Artificial Intelligence Course in London is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings, and assignments anytime and anywhere via the web or your mobile device.
We offer 24/7 support through email, chat, and calls. We have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after the completion of your Artificial Intelligence Course in London.
No refund will be applicable once you make the partial/full payment.
Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in the program on your first attempt. They proactively engage with students to ensure adherence to the learning path—helping to enrich their learning experience, from class onboarding to project mentoring to career assistance
Contact us using the form on the right side of any page on the Simplilearn website, select the Live Chat link, or contact Help & Support.
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