Machine Learning Course in London

Extensive Program with 10 Courses View all
200+ Hours of Interactive Learning
6+ Projects and 40+ Assignments
The capstone project will provide you with a business case. You will need to solve this by applying all the skills you’ve learned in the courses of the master’s program.
Discover your full potential by attending the Machine Learning course in London. In this ML course, you will be taught various techniques and concepts of Machine Learning Using NLP, Python, Deep learning, and PySpark. This Machine learning course in London includes random forests, supervised and unsupervised learning, statistics, machine-learning algorithms, and more. Edureka's Machine learning Course in London offers Capstone projects, Real-time case studies, and 200+ interactive education with lifetime access for those who wish to become Machine Learning engineers.
As per, the average salary for a Machine Learning Engineer is $136,047 per year in United States.

You Will Learn

Python, Statistics, Data Preparation, Machine Learning, Natural Language Processing, Deep Learning, ChatGPT, Reinforcement Learning, Sequence Learning, Image Processing, Computer Vision, Spark MLlib, Data Visualization and many more skills.

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Review for Machine Learning Course in London

Our Masters Course Alumni work for amazing companies


I gained confidence to make a career leap to Data Science after this course

I had a wonderful learning experience with Edureka. Not only did I get exposed to Data Science, but I was also able to learn related technologies that helped me in my career. The course also gave me an edge over other candidates when I was looking for a job change and helped me ace my interviews. I am now planning to shift my career to Data Science and Edureka's course has given me the knowledge and confidence to make this career leap.

Machine Learning Course in London Syllabus

Python Statistics for Data Science Course


The Python Statistics for Data Science course is designed to provide learners with a comprehensive understanding of how to perform statistical analysis and make data-driven decisions. Through a series of interactive lessons and hands-on exercises, you will learn how to conduct hypothesis testing, perform regression analysis, and many more. This course is ideal for anyone looking to enhance their data science skills and gain a deeper understanding of statistics. This course will provide you with the knowledge you need to succeed in the rapidly growing field of data science.

  • WEEK 3-4
  • 6 Modules
  • 12 Hours
  • 6 Skills
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Python Statistics for Data Science Course

Python Programming Certification Course


Edureka’s Python Training Course online is created by experienced professionals to match the current industry requirements and demands. This Python Bootcamp Course will help you master Python programming concepts such as Sequences and File Operations, Conditional statements, Functions, Loops, OOPs, Modules and Handling Exceptions, various libraries such as NumPy, Pandas, Matplotlib, and also focuses on GUI Programming, Web Maps, Data Operations in python and more. Throughout this online Python Course, you will be working on real-time projects and this course will prepare you to clear PCEP, PCAP and PCPP Professional  Certification Exams to become a certified programmer and kick start your career.

  • WEEK 4-5
  • 11 Modules
  • 30 Hours
  • 11 Skills
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Python Programming Certification Course

Data Science with Python Certification Course


Edureka's Data Science with Python Certification Course is accredited by NASSCOM, aligns with industry standards, and is approved by the Government of India. This Data Science with Python course will teach you fundamental to advanced Data Science concepts such as data operations, file operations, object-oriented programming, Pandas, Numpy, and Matplotlib. Regression, clustering, decision trees, random forests, Nave Bayes, statistics, time series, supervised, unsupervised, and reinforcement learning methods will also be covered. This course suits professionals and beginners and will help you launch your data science and machine learning career.

  • WEEK 6-7
  • 12 Modules
  • 36 Hours
  • 12 Skills
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Data Science with Python Certification Course

Artificial Intelligence Certification Course


Edureka’s Advanced Artificial Intelligence Course helps you master essentials of text processing and classifying texts along with important concepts such as Tokenization, Stemming, Lemmatization, POS tagging and many more. You will learn to perform image pre-processing, image classification, transfer learning, object detection, computer vision and also be able implement popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. This course is curated by the industry experts after an extensive research to meet the latest industry requirements and demands. Unleash the power of Artificial Intelligence and accelerate your career— join the global revolution now!

  • WEEK 8-9
  • 18 Modules
  • 42 Hours
  • 18 Skills
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Artificial Intelligence Certification Course

ChatGPT Complete Course: Beginners to Advanced


Edureka’s ChatGPT Course will help you effectively interact with the biggest revelation in the generative AI domain- ChatGPT. You will be able to upgrade your prompt engineering skills, integrate ChatGPT plugins and ChatGPT APIs to enhance your efficiency. Unlock your potential by crafting your very own chatbot, harnessing the knowledge gained from real-life applications and projects covered in this course, and taking a sneak peek into the future with GPT-4 and ChatGPT Plus. Embrace this chance to enhance your skills and distinguish yourself in the ever-evolving digital marketplace!

  • WEEK 3-4
  • 9 Modules
  • 18 Hours
  • 9 Skills
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ChatGPT Complete Course: Beginners to Advanced

PySpark Certification Training Course


Edureka’s PySpark certification training is curated by top industry experts to help you master skills that are required to become a successful Spark developer using Python. This PySpark training will help you to master Apache Spark and the Spark ecosystem, which includes Spark RDDs, Spark SQL, Spark Streaming and Spark MLlib along with the integration of Spark with other tools such as Kafka and Flume. Our PySpark online course is live, instructor-led & helps you master key PySpark concepts with hands-on demonstrations. This PySpark training is fully immersive, where you can learn and interact with the instructor and your peers. Enroll now with this course to learn from top-rated instructors.

  • WEEK 6-7
  • 12 Modules
  • 36 Hours
  • 13 Skills
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PySpark Certification Training Course

Free Elective Courses along with learning path

Self Paced

Python Scripting Certification Training

Self Paced

Reinforcement Learning

Self Paced

Graphical Models Certification Training

Self Paced

Sequence Learning Certification Training


Machine Learning Course Fee in London

1,139 2,271
Your total savings: 1,132
No Cost EMI Available, Starting from 127/mo.
To make this a No Cost EMI offer
The interest amount will be discounted from the price of your order. You will be charged for the item price minus the discounted interest.
See Course Bundle
  • Python Statistics for Data Science Course
  • Python Programming Certification Course
  • Data Science with Python Certification Course
  • Artificial Intelligence Certification Course
  • ChatGPT Complete Course: Beginners to Advanced
  • PySpark Certification Training Course
+4 Free Elective Courses 397

Financing Options

Financing options available without any credit/debit card. The interest amount will be discounted from the price of the course and will be borne by Edureka. You will be charged the course price minus the interest.

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Capstone Project

AI and Machine Learning Engineer Master Capstone Project

The objective of this project is to automatically recognize human actions based on analysis of the body landmarks from pose estimation. 

Machine Learning Course Certification in London

Edureka’s Certificate Holders work at companies like :

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Machine Learning Engineer
Python Statistics for Data Science Course Python Programming Certification Course Data Science with Python Certification Course Artificial Intelligence Certification Course ChatGPT Complete Course: Beginners to Advanced PySpark Certification Training Course AI and Machine Learning Engineer Master Capstone Project
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Features of Machine Learning Course in London

As per your convenience

Weekday or weekend; morning or evening. Multiple options for everyone.

Never miss a class

You can always switch to another batch, depending upon your availability.

24x7 Support

Resolved All Your Doubts Instantly, get One-On-One Learning Assistance Round The Clock.

Lifetime Access

You'll have the keys to all our presentations, quizzes, installation guides. All for a lifetime!

Machine Learning Job Outlook


12 million Career Opportunities estimated for experienced Machine Learning Engineers in the IT industry across the globe.


Salary Trend The average salary for a Machine Learning Engineer is $136,047 per year.


22.00% Annual Growth in job opportunities for Machine Learning Engineers by 2023, worldwide.

    Top Industries
  • Information Technology
  • Finance
  • Retail
  • Manufacturing
  • E-commerce
  • Media & Entertainment
  • Healthcare
    Job Titles include
  • Machine Learning Engineer
  • Data Scientist
  • Artificial Intelligence (AI) Research Scientist
  • Computer Vision Engineer
  • Natural Language Processing (NLP) Engineer
  • Deep Learning Engineer

Machine Learning Course in London FAQ's

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that would typically require human intelligence to complete. These tasks may include recognizing speech, making decisions, understanding natural language, recognizing images or patterns, and playing games, among others. AI involves the use of algorithms, statistical models, and computational techniques to enable machines to learn from experience, identify patterns and insights, and make decisions. AI systems may be designed to work autonomously, or they may be designed to work alongside humans to augment their capabilities and enhance their decision-making abilities. There are several subfields of AI, including machine learning, natural language processing, computer vision, robotics, and expert systems. AI has numerous applications across various industries, including healthcare, finance, transportation, and entertainment
Machine Learning (ML) is a subfield of Artificial Intelligence (AI) that involves the development of algorithms and statistical models that enable computer systems to learn from and make decisions based on data without being explicitly programmed. The goal of ML is to enable machines to learn from experience and improve their performance on a given task over time. ML algorithms can be trained on large datasets of examples, allowing them to identify patterns, relationships, and insights that may not be immediately apparent to human analysts. There are several types of ML algorithms, including supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on labeled data, where the correct output is known for each input. Unsupervised learning involves training a model on unlabeled data, where the algorithm must identify patterns and structures on its own. Reinforcement learning involves training a model to make decisions based on a reward system, where the algorithm learns through trial and error. ML has numerous applications across various industries, including natural language processing, computer vision, speech recognition, recommendation systems, fraud detection, and predictive maintenance, among others.

A Machine Learning Engineer is a professional who designs, develops, and maintains machine learning (ML) systems and applications. Machine learning engineers have a strong background in computer science, mathematics, and statistics and possess the technical skills needed to develop and deploy ML models.

Their primary responsibility is to build and deploy machine learning models that can learn from and make predictions on large datasets. They work with data scientists, software engineers, and other professionals to develop end-to-end ML systems that can be integrated into applications and workflows. This may involve selecting the appropriate algorithms, fine-tuning models, and deploying them in a production environment.

Machine Learning Engineers also have to keep up with the latest developments in ML and AI technologies, research and experiment with new algorithms and techniques, and continuously optimize and improve their ML models to achieve better performance.

AI and Machine Learning Course in London is a structured learning path recommended by leading industry experts and ensures that you transform into a proficient Machine Learning Engineer. Being a full fledged Machine Learning Engineer requires you to master multiple technologies and this program aims at providing you an in-depth knowledge of the entire Machine Learning practices. Individual courses at Edureka focus on specialization in one or two specific skills, however, if you intend to become a master in AI and Machine Learning then this is your go to path to follow.

There are several reasons why someone may choose to become a machine learning engineer:

  1. High Demand: There is a high demand for Machine Learning Engineers in the current job market, with many companies looking to incorporate machine learning technologies into their business processes.
  2. Lucrative Salaries: Machine Learning Engineers are paid well, with some of the highest salaries in the tech industry.
  3. Advancement Opportunities: Machine Learning is a rapidly growing field, and there are plenty of opportunities for career advancement and professional development.
  4. Interesting Work: Machine Learning Engineers work on exciting projects that involve developing and implementing cutting-edge technologies, such as self-driving cars, intelligent virtual assistants, and predictive maintenance systems.
  5. Positive Impact: Machine Learning Engineers can make a significant impact on society by developing systems that can solve complex problems and improve people's lives.
  6. Cross-Disciplinary Skill Set: Machine Learning Engineers possess a cross-disciplinary skill set that includes computer science, mathematics, and statistics, which can be applied to a wide range of fields and industries.
AI and Machine Learning Course in London has been curated after thorough research and recommendations from industry experts. It will help you differentiate yourself with multi-platform fluency, and have real-world experience with the most important tools and platforms. Edureka will be by your side throughout the learning journey - We’re Ridiculously Committed.
Our commitment to equip you with a 360-degree understanding of AI and Machine Learning Courses in London means we cover a broad array of topics to ensure you become a proficient machine learning engineer. Topics covered but not limited to will be:Python, Statistics, Data Preparation, Machine Learning, Natural Language Processing, Deep Learning, Reinforcement Learning, Sequence Learning, Image Processing, Computer Vision, Spark MLlib, Data Visualization and many more skills.
There are no prerequisites for enrollment to this Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Machine Learning, this masters program is designed and developed to accommodate various professional backgrounds.

The roles and responsibilities of machine learning engineers may vary depending on the organization, but some common tasks and responsibilities include:

  1. Data Collection and Preprocessing: Machine Learning Engineers collect and preprocess large datasets to prepare them for analysis and modeling.
  2. Model Selection and Design: They select appropriate models and design experiments to evaluate their performance.
  3. Model Training and Validation: Machine Learning Engineers train and validate models using various algorithms and techniques, such as supervised and unsupervised learning.
  4. Hyperparameter Tuning: They optimize models by tuning hyperparameters to achieve better performance.
  5. Deployment and Integration: Machine Learning Engineers deploy models in a production environment and integrate them into applications and workflows.
  6. Performance Monitoring: They monitor models in real-time to ensure that they are performing well and making accurate predictions.
  7. Algorithm Development: Machine Learning Engineers develop and implement new algorithms and techniques to improve model accuracy and performance.
  8. Collaborating with Other Teams: They collaborate with data scientists, software engineers, and other professionals to develop end-to-end ML systems.
  9. Staying Up-to-Date with the Latest Developments: Machine Learning Engineers keep up-to-date with the latest developments in ML and AI technologies, research and experiment with new algorithms and techniques, and continuously optimize and improve their ML models.
Edureka’s AI and Machine Learning Course in London is a thoughtful compilation of Instructor-led and Self-paced Training Program, allowing the learners to be guided by industry experts and learn skills at their own pace.
Yes! You can be enrolled in multiple other Instructor-led or Self-paced courses offered by Edureka. This is the advantage of learning with us - “Flexible Schedule”. You can select the batches that allow you to make the best of your learning journey without the fear of overlapping or missing classes.
As soon as you enroll, all the 10 courses mentioned in the curriculum will be added to your account. Edureka provides its learners with immediate and lifetime access to every course, which is a part of the AI and Machine Learning Masters Course.

The Machine Learning Engineer training course in London is for those who want to fast-track their AI and Machine Learning career. This AI and Machine Learning Masters Course will benefit the people working in the following roles:

  • Freshers
  • Data Science professionals
  • Machine Learning professional
  • AI professionals
  • Analytics professionals
  • Business Analysts
  • Software Developers
On completing this Who should take this AI and Machine Learning Course in London, you’ll be eligible for the roles like: Machine Learning Engineer, Data Scientist, Artificial Intelligence (AI) Research Scientist, Computer Vision Engineer, Natural Language Processing (NLP) Engineer, Deep Learning Engineer, and many more.

Several companies in London are actively hiring machine learning professionals. Some prominent companies in the field include:

  • DeepMind
  • Google
  • Facebook
  • Amazon
  • Microsoft
  • Barclays
  • ASOS
  • Deliveroo
  • Expedia
  • King (part of Activision Blizzard)
  • With machine Learning certification training in London, you can expect to work on various projects that focus on real-world applications of Machine Learning. These projects may include tasks such as:

  • Predictive Modeling: Building models to predict outcomes or make forecasts based on historical data. For example, predicting customer churn, stock market trends, or disease diagnosis.
  • Image or Text Classification: Develop models to classify images or text into different categories. This can include tasks like spam detection, sentiment analysis, or object recognition.
  • Recommendation Systems: Creating algorithms that provide personalized recommendations based on user preferences or behaviour. This can be applied to e-commerce, movie recommendations, or music streaming platforms.
  • Anomaly Detection: Developing models to identify unusual patterns or outliers in data, which can be useful in fraud detection, network security, or equipment failure prediction.
  • Natural Language Processing (NLP): Working on projects that involve processing and understanding human languages, such as language translation, chatbots, or sentiment analysis.
  • Time Series Analysis: Analyzing and forecasting data that changes over time, commonly used in areas like finance, stock market prediction, or weather forecasting.
  • These are just a few examples, and the projects in applied Machine Learning certification training can vary depending on the program and curriculum. The aim is to provide hands-on experience in solving real-world problems using Machine Learning techniques and methodologies.

    The salary of a machine learning professional in London can vary depending on factors such as experience, skills, industry, and company size. The average salary range for machine learning roles in London is between £40,000 and £100,000 per year. Senior-level positions or roles in larger organisations may offer higher salaries.
    The cost of a machine learning course in London is £ 1,139.

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