Learn machine learning in London with Python, NumPy, Pandas, Scikit-learn, TensorFlow/Keras, and Flask basics. Build practical models, work through real datasets, and understand the full ML workflow from preprocessing to deployment.
14,200+ (Placed)
Freshers to IT
7,100+ (Placed)
Non-IT to Tech
5,800+ (Placed)
Career Gap Fillers
6,400+ (Placed)
Upskilling Success
24,999₹
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5.2 LPA • ServiceNow Developer
5.7 LPA • Android Developer
6 LPA • Android Developer
7 LPA • Android Developer
9 LPA • AI Engineer
5 LPA • Data Scientist
8 LPA • Machine Learning Engineer
4 LPA • AI Engineer
4 LPA • Associate Product Manager
3.45 LPA • Network Engineer
3.75 LPA • NOC Support Engineer
4.4 LPA • Network Administrator
9 LPA • AI Engineer
12 LPA • Data Engineer
16 LPA • Data Engineer
5.1 LPA • RPA Developer
7.83 LPA • RPA Business Analyst
5.55 LPA • Data Scientist
40 LPA • AWS Devops Engineer
25 LPA • Salesforce Developer
30 LPA • Project Administrator
20 LPA • Digital Marketing Specialist
12 LPA • Social Media Manager
8 LPA • Digital Marketing Analyst
8.5 LPA • Performance Marketer
4.3 LPA • Digital marketing specialist
8 LPA • Performance Marketer
4.3 LPA • AI Engineer
7.5 LPA • Data Engineer
4.5 LPA • Salesforce Developer
8.45 LPA • Computer Vision Engineer
5 LPA • SAP FICO Analyst
5.8 LPA • SAP FICO Analyst
4.2 LPA • Servicenow Developer
4.8 LPA • TOSCA Automation Engineer
8 LPA • Data Engineer
8 LPA • Tosca Test Analyst
10 LPA • Machine Learning Engineer
4.4 LPA • Tosca Administrator
5.7 LPA • ML Engineer
6 LPA • Devops Engineer
7.15 LPA • DevSecOps Engineer
6.3 LPA • AI Engineer
7 LPA • MLOps Engineer
5 LPA • HR Executive
7 LPA • Data Scientist
10 LPA • Brand Marketing Specialist
8.2 LPA • AI Engineer
Learning machine learning is only one part of getting hired. Inventateq adds placement support so you can present your Python work, ML projects, and tool knowledge clearly for London-based roles.
London hiring spans tech, fintech, healthcare, retail, and analytics teams that use machine learning for prediction, segmentation, and automation. Salaries usually rise as you move from model building to deployment, infrastructure, and lead responsibilities.
Machine Learning Average Salary by Experience
London hiring spans tech, fintech, healthcare, retail, and analytics teams that use machine learning for prediction, segmentation, and automation. Salaries usually rise as you move from model building to deployment, infrastructure, and lead responsibilities.
Machine Learning Average Salary by Experience
4.7/5 Google Rating | 1,432+ Verified Reviews
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Success Result: Our students are competing at global levels. Watch their placement journey here.
Data Engineering @ Accenture - 12 LPA
Junior Accountant @ Fortis - 8 LPA
SQL Developer @ Wipro - 10 LPA
Salesforce Administrator @ Deloitte - 15 LPA
RPA Developer @ IBM - 20 LPA
Tableau Developer @ Genpact - 20 LPA
Talent Acquisition Executive @ Tech Mahindra - 12 LPA
Angular Developer @ Capgemini - 15 LPA
Data Analyst @ Amazon - 25 LPA
Java Developer @ Oracle - 25 LPA
CATIA Design Engineer @ TATA Motors - 20 LPA
AWS Solutions Architect @ Accenture - 25 LPA
Python Developer @ Mphasis - 15 LPA
QA Engineer @ HCLTech - 15 LPA
Cloud DevOps Engineer @ LTIMindtree - 18 LPA
Digital Marketer @ Google - 20 LPA
BTM Layout @ Inventateq - -
Genuine Reviews @ Inventateq - 25 LPA - 50LPA
Data Engineering @ Accenture - 12 LPA
Junior Accountant @ Fortis - 8 LPA
SQL Developer @ Wipro - 10 LPA
Salesforce Administrator @ Deloitte - 15 LPA
RPA Developer @ IBM - 20 LPA
Tableau Developer @ Genpact - 20 LPA
Talent Acquisition Executive @ Tech Mahindra - 12 LPA
Angular Developer @ Capgemini - 15 LPA
Data Analyst @ Amazon - 25 LPA
Java Developer @ Oracle - 25 LPA
CATIA Design Engineer @ TATA Motors - 20 LPA
AWS Solutions Architect @ Accenture - 25 LPA
Python Developer @ Mphasis - 15 LPA
QA Engineer @ HCLTech - 15 LPA
Cloud DevOps Engineer @ LTIMindtree - 18 LPA
Digital Marketer @ Google - 20 LPA
BTM Layout @ Inventateq - -
Genuine Reviews @ Inventateq - 25 LPA - 50LPA
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4.7/5 · 1,432+ Verified Reviews
Inventateq keeps the machine learning course practical from the first module. You start with ML basics and Python, then move into preprocessing, supervised and unsupervised learning, model evaluation, feature engineering, and deployment basics with real tools.
We stand apart through our commitment to:
Our live online machine learning training in London follows the same syllabus and project flow as the classroom batch. You can join from home, learn in real time, and complete Python, Scikit-learn, and deployment exercises with trainer support.
Good for learners who want a clear entry into machine learning from Python and basic statistics.
Useful for analysts, software learners, and engineers who want to move into ML and AI roles.
Helps freshers build project-based machine learning skills for job applications.
Suitable if you want a structured start and can follow the Python and math foundations.
Ideal for people moving into data science, machine learning, or AI development roles.
Duration: Structured training with a complete machine learning syllabus
Mode: Offline classroom and live online options
Practice: Hands-on sessions using Python and ML libraries
Projects: Real-world project work built into the course
No prior ML experience is required to begin this course.
Rated 4.9/5
Inventateq focuses on building usable machine learning skills that map to real job roles. The training stays practical, with Python, model building, evaluation, feature engineering, and deployment basics taught through projects.
By the end of the course, learners can handle datasets, build models, evaluate performance, and prepare basic ML applications. The course also gives practice with the tools and project formats employers expect.
You learn how to move from a dataset to a working model using Python, preprocessing, and supervised learning methods.
You practice missing values, encoding, scaling, feature selection, and train-test splits the way ML work is done in practice.
You learn how to read accuracy, precision, recall, F1 score, and confusion matrices before tuning a model.
The course includes house price prediction, spam detection, customer segmentation, and disease prediction examples.
You get an introduction to saving models, Flask/FastAPI basics, APIs, and cloud deployment concepts.
Resume support and interview preparation help you explain your work with confidence in machine learning roles.
This certification shows that you have completed structured training in machine learning concepts, Python-based modeling, evaluation, and deployment basics. It helps employers see that you have trained on both the theory and the tools used in entry-level ML work.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Yes. The course begins with machine learning basics, Python for ML, and the math needed to understand models. It is suitable for beginners who want a structured start in London.
Yes. The syllabus includes house price prediction, spam email detection, customer segmentation, and disease prediction model work. These projects help you practice the concepts in a practical way.
Yes. Inventateq supports resume preparation, portfolio guidance, mock interviews, and career direction for roles like Machine Learning Engineer and Data Scientist. The support is tied to your course projects and tools.
Yes, if you are willing to learn Python and basic statistics step by step. The course is designed to introduce the essential foundations before moving into modeling and deployment basics. Mentor support helps you stay on track.
Yes. You can attend live online classes and follow the same syllabus as the classroom batch. It is a practical option if you want flexibility while studying from London.
The course is structured across multiple modules covering fundamentals, Python, preprocessing, modeling, evaluation, feature engineering, deep learning basics, deployment, and projects. Exact batch timing can vary by schedule. You can choose a format that fits your learning plan.
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