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Gen AI And Machine Learning Training in London

Q: Does ACTE provide placement?

ACTE provides placement support, mock interviews, presentation skills, career guidance, and access to job openings and learning resources through the Student Portal.

Q: Does the GENAI & MACHINE LEARNING course include practical projects?

Learners work on practical projects involving generative AI applications, large language models, prompt engineering, machine learning algorithms, AI integration, and intelligent application development.

Q: Which training formats are offered for GENAI & MACHINE LEARNING Certification in London?

Training formats may include classroom training, online classes, individual mentoring, fast-track batches, and flexible learning options.

Q: Which certificate will I receive after completing the course?

Participants may receive an ACTE course completion certificate documenting their training, participation, and acquired GENAI & MACHINE LEARNING skills.

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Advance Your Career With Gen AI And Machine Learning Training In London And Develop Skills.
Build Expertise Through Practical Labs And Industry-Based Gen AI And Machine Learning Projects.
Get Career Support And Placement Guidance To Explore Suitable Employment Opportunities.
Strengthen Job-Ready Skills Through Practical Projects And Convenient Learning Schedules.

Job Assistance

1,200+ Enrolled

In collaboration with

65+ Hrs.

Duration

Online/Offline

Format

LMS

Life Time Access

10k+ Placed Students Download Curriculum Interview Questions

Quality Training With Affordable Fee

⭐ Fees Starts From

INR ~~36,000~~

INR 16,500

100% Placements | Get Hired in Top MNC

Our Hiring Partners

Explore Career-Focused GENAI & MACHINE LEARNING Training in London

GENAI & MACHINE LEARNING training in London offers practical knowledge of generative AI, machine learning, Python, AI models, and application development. Learners develop skills required to build intelligent applications and explore AI-driven solutions.
The course includes practical learning through demonstrations, guided activities, assignments, and projects. Participants practice prompt engineering, model integration, application development, data processing, evaluation, and deployment concepts using relevant tools.
Practical projects help learners understand generative AI workflows, machine learning algorithms, data preparation, model evaluation, prompt optimization, and AI application development. Participants gain experience building practical AI-based solutions.
Participants receive career-focused assistance through resume development, mock interviews, technical interview preparation, job guidance, and professional mentoring. The program prepares candidates for roles such as Generative AI Engineer, Machine Learning Engineer, and AI Developer.
The GENAI & MACHINE LEARNING training in London covers generative AI fundamentals, large language models, prompt engineering, machine learning techniques, and application integration. This helps participants develop practical capabilities for modern AI technology environments.
A structured learning approach combines practical assignments, projects, revision sessions, and expert guidance to strengthen GENAI & MACHINE LEARNING knowledge. Participants build technical confidence through project experience while preparing for certification and suitable career opportunities.

Essential Skills You Can Build Through GENAI & MACHINE LEARNING Course in London

Build a strong GENAI & MACHINE LEARNING foundation by learning Python, generative AI fundamentals, machine learning concepts, and large language models.

Learn AI application development techniques including prompt engineering, model integration, evaluation, data processing, and practical AI workflows.

Develop practical abilities to build generative AI applications, integrate AI models, evaluate outputs, and create intelligent technology solutions effectively.

Learn to apply GENAI & MACHINE LEARNING techniques through practical projects covering AI automation, predictive modeling, and business solutions.

Your IT Career Starts Here

550+ Students Placed Every Month!

Get inspired by their progress in the Career Growth Report.

Other Categories Placements

Non-IT to IT (Career Transition) 2371+
Diploma Candidates3001+
Non-Engineering Students (Arts & Science)3419+
Engineering Students3571+
CTC Greater than 5 LPA4542+
Academic Percentage Less than 60%5583+
Career Break / Gap Students2588+

Top Placement Record

Upcoming Batches For Classroom and Online

Weekdays

19 - Oct - 2026

08:00 AM & 10:00 AM

Weekdays

21 - Oct - 2026

08:00 AM & 10:00 AM

Weekends

24 - Oct - 2026

(10:00 AM - 01:30 PM)

Weekends

25 - Oct - 2026

(09:00 AM - 02:00 PM)

Can't find a batch you were looking for?

INR 16,500

INR ~~36,000~~

OFF Expires in

BOOK A FREE DEMO CLASS

Who Should Take A Gen AI And Machine Learning Certification Training

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Working Professionals

Diploma Holders

Professionals from Other Fields

Salary Hike

Graduates with Less Than 60%

Job Roles For Gen AI And Machine Learning Certification Course

HCM Reporting Analyst

Solution Architect

HCM Project Lead

Workforce Consultant

HCM Integration Consultant

HCM Support Analyst

HCM Functional Consultant

HCM Tech Consultant

What’s included ?

📊 Free Aptitude and Technical Skills Training

Learn basic maths and logical thinking to solve problems easily.
Understand simple coding and technical concepts step by step.
Get ready for exams and interviews with regular practice.

🛠️ Hands-On Projects

Work on real-time projects to apply what you learn.
Build mini apps and tools daily to enhance your coding skills.
Gain practical experience just like in real jobs.

🧠 Launch Your Career in Top MNC Companies

Master technical and HR interview rounds.
Gain confidence with expert mock interview practice.
Improve your chances of getting hired faster.

🎯 Interview Preparation For Freshers

Practice company-based interview questions.
Take online assessment tests to crack interviews
Practice confidently with real-world interview and project-based questions.

🧪 LMS Self Learning Platform

Explore expert trainer videos and documents to boost your learning.
Study anytime with on-demand videos and detailed documents.
Top MNC interview questions & self coding practice.

Pure Practical & Job Oriented GENAI & MACHINE LEARNING Certification Online Training Course Details

Syllabus of GENAI & MACHINE LEARNING Certification Course in London

Module 1: Introduction to Generative AI and Machine Learning

Introduction to Artificial Intelligence
Overview of Generative AI
Fundamentals of Machine Learning
Applications of Generative AI
Types of Machine Learning
AI Development Environments
Python Programming Fundamentals
Python Data Types and Variables
Control Flow and Functions
Python Libraries for AI
Introduction to NumPy
Introduction to Pandas
Data Processing Fundamentals
Introduction to Scikit-Learn
Machine Learning Workflows
Data Collection Techniques
Data Cleaning and Preparation
Exploratory Data Analysis
Statistical Concepts for Machine Learning
Feature Engineering Fundamentals
Model Training and Testing
Understanding Training and Validation Data
Model Evaluation Fundamentals
Introduction to AI Development Tools
Setting Up Python Environments
Working with Jupyter Notebook
AI Project Development Fundamentals
Understanding Real-World AI Applications
Introduction to Responsible AI
Overview of AI Career Opportunities

Module 2: Python Programming and Machine Learning Algorithms

Python Variables and Data Types
Conditional Statements
Loops and Iterations
Functions and Modules
Lists, Tuples, Sets, and Dictionaries
String Manipulation
File Handling
Exception Handling
NumPy Arrays and Operations
Pandas DataFrames and Series
Data Import and Export
Data Transformation Techniques
Introduction to Machine Learning Algorithms
Linear Regression
Logistic Regression
Decision Tree Algorithms
Random Forest Algorithms
K-Nearest Neighbors
Support Vector Machines
Naive Bayes Classification
K-Means Clustering
Supervised Learning Techniques
Unsupervised Learning Techniques
Training and Testing Machine Learning Models
Cross-Validation Techniques
Model Performance Metrics
Accuracy, Precision, and Recall
Confusion Matrix Analysis
Feature Selection Techniques
Hyperparameter Tuning
Model Optimization Fundamentals
Practical Machine Learning Exercises

Module 3: Deep Learning, Neural Networks and Generative AI

Introduction to Deep Learning
Artificial Neural Networks
Neural Network Architecture
Neurons, Layers, and Activation Functions
Forward Propagation
Backpropagation Fundamentals
Loss Functions and Optimization
Gradient Descent Techniques
Introduction to TensorFlow
Introduction to PyTorch
Deep Learning Model Training
Model Evaluation and Validation
Introduction to Natural Language Processing
Text Preprocessing Techniques
Tokenization and Text Representation
Word Embeddings Fundamentals
Language Model Fundamentals
Introduction to Generative Models
Generative AI Architecture
Transformer Architecture
Attention Mechanisms
Encoder and Decoder Concepts
Pretrained Language Models
Large Language Model Fundamentals
Text Generation Techniques
AI Content Generation
Generative AI Use Cases
AI Model Limitations
Evaluating Generative AI Outputs
Practical Deep Learning Exercises

Module 4: Large Language Models and Prompt Engineering

Introduction to Large Language Models
LLM Architecture and Fundamentals
Pretrained Models and Fine-Tuning Concepts
Understanding Tokens and Context Windows
Prompt Engineering Fundamentals
Writing Effective Prompts
Instruction-Based Prompting
Zero-Shot Prompting
Few-Shot Prompting
Chain-of-Thought Prompting Concepts
Role-Based Prompting
Structured Output Generation
Prompt Templates and Variables
Prompt Optimization Techniques
Context Management
Controlling AI Responses
Reducing Incorrect AI Outputs
Evaluating Prompt Effectiveness
Comparing Model Responses
Working with LLM APIs
Integrating Language Models into Applications
Managing API Requests and Responses
Introduction to Embeddings
Semantic Search Fundamentals
AI-Powered Information Retrieval
Large Language Model Use Cases
Conversational AI Fundamentals
Prompt Engineering Projects
LLM Application Testing
Responsible Use of Language Models

Module 5: AI Chatbots and Intelligent Application Development

Introduction to AI Chatbots
Chatbot Architecture
Conversational AI Fundamentals
Designing Conversation Flows
Integrating Large Language Models
Connecting AI Models through APIs
Building AI-Powered Chat Applications
Managing User Queries
Context-Aware Conversations
Maintaining Conversation History
Handling Invalid User Inputs
Response Generation and Formatting
AI Application Interface Development
Frontend and Backend Integration
API Request and Response Handling
Error Handling in AI Applications
Authentication Fundamentals
Managing Application Configuration
Working with Environment Variables
Document-Based Chatbot Development
Question Answering Applications
AI Assistant Development
Testing Chatbot Functionality
Evaluating Response Quality
Improving Conversational Accuracy
Chatbot Deployment Fundamentals
Application Performance Monitoring
AI Application Security Fundamentals
Practical Chatbot Development Projects
Real-World Conversational AI Use Cases

Module 6: Retrieval-Augmented Generation and AI Integration

Introduction to Retrieval-Augmented Generation
RAG Architecture and Components
Understanding Retrieval-Based AI Systems
Document Collection and Preparation
Document Loading Techniques
Text Splitting and Chunking
Embedding Generation
Vector Representation of Text
Vector Database Fundamentals
Semantic Search Techniques
Similarity Search
Information Retrieval Techniques
Connecting Retrieved Context to LLMs
Context-Based Response Generation
Document Question Answering
Building Knowledge-Based AI Applications
Introduction to LangChain
LLM Chains and Components
Prompt Templates and Retrieval Chains
AI API Integration
Integrating External Services
Managing Data Sources
Evaluating Retrieval Quality
Reducing Unsupported Responses
RAG Application Testing
RAG Performance Optimization
AI Workflow Integration
Document Processing Applications
Practical RAG Projects
Real-World AI Integration Scenarios

Module 7: AI Automation and Business Applications

Introduction to AI Automation
Business Process Automation Fundamentals
Identifying AI Automation Opportunities
Designing AI-Powered Workflows
Integrating AI with Business Applications
API-Based Workflow Automation
Automating Text Processing Tasks
Automated Document Summarization
Information Extraction Using AI
Automated Classification and Categorization
AI-Based Content Generation
Intelligent Email Processing
AI-Assisted Data Analysis
Workflow Triggers and Actions
Managing Workflow Inputs and Outputs
Handling Automation Errors
Human Review and Approval Workflows
Monitoring Automated Processes
Evaluating Automation Performance
Business Productivity Applications
Customer Support Automation
AI-Powered Knowledge Assistants
Integrating External Data Sources
AI Automation Limitations
Responsible AI Automation Practices
Workflow Security Fundamentals
Automation Testing and Validation
Practical AI Automation Exercises
Business-Oriented AI Projects
Industry Use Cases and Case Studies

Module 8: Model Evaluation, Fine-Tuning and Optimization

Introduction to Model Evaluation
Evaluating Machine Learning Models
Classification and Regression Metrics
Model Validation Techniques
Overfitting and Underfitting
Hyperparameter Optimization
Feature Selection and Engineering
Machine Learning Pipeline Optimization
Evaluating Large Language Model Outputs
AI Response Quality Assessment
Factual Accuracy and Relevance
Consistency and Completeness of Responses
Evaluating Prompt Performance
Comparing Language Model Outputs
Introduction to Fine-Tuning
Fine-Tuning Fundamentals
Preparing Training Datasets
Training Data Quality and Validation
Transfer Learning Concepts
Parameter-Efficient Fine-Tuning Concepts
Model Selection and Comparison
Inference Performance Optimization
Latency and Resource Considerations
Monitoring AI Application Performance
Identifying Model Limitations
Testing Edge Cases
Evaluating AI Safety and Reliability
Optimization Strategies for AI Applications
Practical Model Evaluation Exercises
Model Improvement Case Studies

Module 9: AI Deployment, Security and Responsible AI

Introduction to AI Application Deployment
Preparing Applications for Deployment
Deployment Environment Configuration
Managing Application Dependencies
Environment Variables and Configuration
API Deployment Fundamentals
Cloud-Based AI Application Concepts
Containerization Fundamentals
Introduction to Docker
Application Testing Before Deployment
Monitoring AI Applications
Logging and Error Tracking
Performance and Resource Monitoring
AI Application Maintenance
Authentication and Authorization
API Key Management
Data Privacy Fundamentals
Secure Handling of User Inputs
AI Application Security Risks
Prompt Injection Awareness
Managing Sensitive Information
Responsible AI Principles
Bias and Fairness in AI Systems
Transparency and Explainability
Human Oversight of AI Outputs
Evaluating AI Reliability
Deployment Troubleshooting
AI Application Maintenance Workflows
Deployment and Security Exercises
Responsible AI Case Studies

Module 10: GENAI & MACHINE LEARNING Projects and Career Preparation

Introduction to Industry-Oriented AI Projects
Project Planning and Requirement Analysis
Dataset Selection and Preparation
Machine Learning Model Development
AI Chatbot Development
Large Language Model Integration
Prompt Engineering Project
Document Question Answering Application
Retrieval-Augmented Generation Project
AI-Powered Content Generation
Intelligent Business Assistant Development
AI-Based Text Classification
Machine Learning Prediction Project
AI Workflow Automation Project
End-to-End AI Application Development
Frontend and Backend Integration
API Integration and Testing
Model Evaluation and Validation
Application Deployment
Project Documentation
Technical Report Preparation
Project Demonstration and Presentation
Industry Case Study Discussions
Portfolio Development
Resume Preparation
Technical Interview Preparation
Generative AI Interview Questions
Machine Learning Interview Practice
Mock Interviews and Feedback
Career Guidance and Placement Preparation

Show Less

GENAI & MACHINE LEARNING Course Learning Objectives

What qualifications are needed to join GENAI & MACHINE LEARNING Training in London?

GENAI & MACHINE LEARNING does not require a specific educational qualification. Learners with basic computer knowledge, logical thinking, and an interest in artificial intelligence can understand AI concepts effectively. Basic programming and mathematics knowledge can also support the learning process.

Is programming knowledge needed for a GENAI & MACHINE LEARNING certification course?

Basic programming knowledge can be useful when learning GENAI & MACHINE LEARNING, particularly for application development. The course covers generative AI, machine learning algorithms, Python, large language models, prompt engineering, model integration, and introductory AI application development through practical sessions.

What are the main objectives of the GENAI & MACHINE LEARNING training institute in London?

The primary objective of GENAI & MACHINE LEARNING training is to help learners understand generative AI, machine learning, intelligent application development, and AI model integration. Participants learn Python, large language models, prompt engineering, machine learning techniques, application development, and deployment concepts using practical exercises and AI scenarios.

Who can benefit from a GENAI & MACHINE LEARNING course in London?

GENAI & MACHINE LEARNING training can benefit learners from various academic and professional backgrounds. IT professionals, developers, software engineers, data analysts, AI professionals, engineering graduates, working professionals, and freshers can develop practical artificial intelligence skills.

What are the benefits of GENAI & MACHINE LEARNING internship training?

Learning GENAI & MACHINE LEARNING can provide several professional benefits:

Improves practical generative AI abilities.
Builds machine learning application development skills.
Introduces important prompt engineering techniques.
Enhances AI model integration skills.
Supports pathways toward AI-focused careers.

What career opportunities are available after a GENAI & MACHINE LEARNING course in London?

GENAI & MACHINE LEARNING skills can support opportunities in technology, finance, healthcare, retail, e-commerce, manufacturing, consulting, and other AI-oriented industries. Depending on their skills and experience, learners can explore roles related to generative AI development, machine learning engineering, AI application development, and AI integration. Practical project experience can help candidates showcase their capabilities.

How can a fresher start a career after GENAI & MACHINE LEARNING placement course?

Learn essential generative AI concepts.
Study Python and machine learning fundamentals.
Practice prompt engineering and AI integration.
Understand large language models and AI workflows.
Develop practical GENAI & MACHINE LEARNING portfolio projects.

Who can register for this GENAI & MACHINE LEARNING Certification training?

The program is suitable for individuals interested in developing artificial intelligence, machine learning, programming, and AI application development skills:

IT and Software Professionals.
Developers and Data Analysts.
AI and Machine Learning Professionals.
Engineering and Technical Graduates.
Freshers and Working Professionals.

Which career roles can I pursue after completing GENAI & MACHINE LEARNING training?

After developing relevant technical and artificial intelligence skills, learners can explore various GENAI & MACHINE LEARNING career paths:

Generative AI Engineer.
Machine Learning Engineer.
AI Application Developer.
AI Engineer.
Prompt Engineer.

Which skills are covered in a GENAI & MACHINE LEARNING course?

Generative AI Fundamentals.
Python and Machine Learning.
Large Language Models and Prompt Engineering.
AI Application Development and Integration.
Model Evaluation and Deployment Concepts.

Why should I choose a GENAI & MACHINE LEARNING course in London?

GENAI & MACHINE LEARNING helps organizations develop intelligent applications, automate tasks, improve workflows, and support business operations. Professionals can integrate AI models, develop generative AI applications, evaluate outputs, implement AI workflows, and optimize application performance. Developing these skills can support adaptation to increasingly AI-driven technology and business environments.

What should I learn in a GENAI & MACHINE LEARNING Certification internship course?

Learners should focus on generative AI fundamentals, Python, machine learning algorithms, large language models, prompt engineering, AI application development, model evaluation, and integration. Practicing AI frameworks, APIs, and application development tools is also useful. Real-world projects help participants apply these concepts and understand complete AI application workflows.

Overview Of GENAI & MACHINE LEARNING Course in London

GENAI & MACHINE LEARNING Course in London is designed for students, IT professionals, developers, engineers, and aspiring AI specialists seeking practical skills in artificial intelligence and machine learning. The program covers Python, generative AI, machine learning algorithms, large language models, prompt engineering, AI application development, API integration, and deployment concepts. Through expert-led sessions, practical exercises, assignments, and industry-oriented projects, participants learn to develop intelligent applications and AI-powered solutions. The GENAI & MACHINE LEARNING Course in London also covers AI fundamentals, model integration, data processing, application testing, model evaluation, and development workflows. Learners work with practical projects and business scenarios to understand complete generative AI workflows from prompt design through model integration and application delivery. Along with technical knowledge, participants receive project guidance, interview preparation, resume support, career counseling, and placement-focused assistance. Completing the program helps learners develop relevant skills for opportunities in Generative AI Development, Machine Learning Engineering, AI Application Development, AI Engineering, and other artificial intelligence-focused technology roles.

Additional Course Information

Professional Roles After GENAI & MACHINE LEARNING Placement Training in London

Generative AI Engineer : Develops generative AI applications, integrates large language models, implements prompt engineering, and builds intelligent solutions for business requirements.
Machine Learning Engineer : Develops machine learning models, prepares datasets, evaluates model performance, implements algorithms, and supports intelligent application functionality.
AI Application Developer : Creates AI-powered applications, integrates AI models and APIs, implements application features, and supports testing and maintenance.
AI Engineer : Develops artificial intelligence solutions, integrates machine learning techniques, automates workflows, and implements AI functionality for practical applications.
Prompt Engineer : Designs and refines prompts, evaluates AI-generated outputs, improves response quality, and develops effective interactions with generative AI models.
AI Integration Developer : Integrates AI models with existing applications, manages API communication, implements application workflows, and supports reliable data exchange between services.

Essential Tools and Technologies Covered in GENAI & MACHINE LEARNING Certification Course in London

Python : Provides programming capabilities for data processing, machine learning workflows, AI application development, automation, and integration with artificial intelligence libraries.
Generative AI : Supports the development of AI-generated text, content creation, intelligent assistants, conversational applications, and solutions for practical business requirements.
Large Language Models : Enable text generation, conversational interactions, content summarization, information extraction, and the development of language-based AI applications.
Prompt Engineering : Helps professionals design effective prompts, improve AI responses, structure instructions, and optimize interactions with generative AI models.
Machine Learning Frameworks : Support model development, data preparation, algorithm implementation, model evaluation, and the creation of predictive and intelligent solutions.
APIs and AI Integration : Enable AI model connectivity, application integration, request-response handling, external service communication, and the development of AI-powered workflows.

Essential Skills Developed Through GENAI & MACHINE LEARNING Training Institute in London

Generative AI Development : Learn to develop AI-powered applications, work with language models, design prompts, integrate AI services, and create intelligent application features.
Machine Learning : Develop knowledge of machine learning algorithms, data preparation, model training, evaluation techniques, and predictive application development.
Prompt Engineering : Design structured prompts, refine instructions, evaluate generated responses, troubleshoot output issues, and improve interactions with AI models.
AI Application Integration : Create and integrate APIs, connect AI models with applications, manage requests and responses, handle errors, and develop functional AI workflows.
Model Evaluation : Evaluate AI-generated outputs, identify limitations, test application functionality, troubleshoot errors, and improve the reliability of AI solutions.
AI Deployment and Maintenance : Deploy AI-powered applications, configure environments, manage integrations, troubleshoot implementation issues, and maintain applications after release.

Career Opportunities After GENAI & MACHINE LEARNING Internship Training in London

Artificial Intelligence Growth : Organizations increasingly use artificial intelligence to automate processes and develop intelligent services, creating opportunities for skilled professionals.
Generative AI Application Development : Businesses require AI-powered assistants, content generation tools, and intelligent applications, increasing the relevance of generative AI development skills.
Machine Learning Across Industries : AI and machine learning skills can be applied in finance, healthcare, e-commerce, manufacturing, technology, and other sectors, creating diverse professional opportunities.
AI and API Integration : Modern applications increasingly use AI models, APIs, and external services, making integration and deployment skills valuable for development teams.
Automation and Intelligent Solutions : AI technologies support workflow automation, data analysis and business operations, creating opportunities for professionals with practical AI knowledge.
Career Advancement : Combining GENAI & MACHINE LEARNING knowledge with software development, data engineering, or AI frameworks can help professionals pursue advanced technical roles.

Need customized curriculum?

Hands-on Real-Time Gen AI Projects

Project 1

AI-Powered Chatbot Development

Develop a generative AI chatbot using large language models to understand user queries, and support interactive conversations for practical business applications.

Project 2

AI-Based Text Summarization

Develop a generative AI application to summarize lengthy documents,and generate concise summaries using natural language processing techniques.

Project 3

Machine Learning-Based Fraud Detection

Analyze transaction datasets to identify suspicious activities model to detect potential fraudulent transactions using relevant classification techniques.

Project 4

AI-Powered Document Question Answering

Develop an AI application that processes uploaded documents, and generates contextual answers to user questions using large language models.

GENAI & MACHINE LEARNING Placement Support in London

GENAI & MACHINE LEARNING Placement Support combines practical assignments, industry-oriented projects, and career-focused learning to develop skills needed for generative AI and machine learning roles.
Career guidance includes resume preparation, interview practice, technical assessments, and expert mentoring to support candidates pursuing GENAI & MACHINE LEARNING career opportunities.
Learners develop practical knowledge of Python, large language models, prompt engineering, machine learning, AI integration, application development, and AI automation through project-based activities.
The training prepares participants for roles including Gen AI Developer, Machine Learning Engineer, AI Automation Specialist, and AI Application Developer across different technology sectors.
Mock interviews, technical practice sessions, communication activities, and personalized mentoring help learners improve professional skills and prepare confidently for recruitment processes.
GENAI & MACHINE LEARNING Placement Support helps eligible learners explore career opportunities with companies such as HCLTech, Wipro, Dell, Accenture, Cognizant, TCS, IBM, and Capgemini.
Career guidance covers job updates, interview coordination, recruiter support, profile improvement, and employment assistance for candidates pursuing GENAI & MACHINE LEARNING career opportunities.

Earn Your Gen AI And Machine Learning Course Certification

Gen AI And Machine Learning Internship Training in London develops practical knowledge of Generative AI technologies and prepares learners for roles such as Gen AI Developer, Prompt Engineer, and AI Automation Specialist. The curriculum explores Large Language Models, intelligent applications, AI chatbots, process automation, and real-world business scenarios. Through practical projects, interactive exercises, and certification preparation, participants strengthen their understanding of emerging AI technologies. The Gen AI And Machine Learning course certificate recognizes training completion and can support professional development while exploring opportunities across the growing artificial intelligence industry in London.

Complete Your Training

Download your course completion certificate in PDF format as soon as you successfully finish the training program.

Obtain Your Certificate

Receive a printed course certificate featuring official branding and security details to acknowledge your training completion.

Get Certified

Learn from Skilled GENAI & MACHINE LEARNING Trainers in London

Our GENAI & MACHINE LEARNING trainers in London have expertise in Generative AI ,large language models, prompt engineering, machine learning, and practical solutions for diverse business needs.
Trainers provide practical guidance in Python programming, generative AI applications, large language models, prompt engineering, AI integration, and techniques applied in industry projects.
The training offers hands-on practice with machine learning algorithms, AI chatbots, intelligent applications, prompt optimization, model evaluation, and AI application development techniques.
Learners explore AI automation, practical datasets, generative AI workflows, model integration, application development, and effective approaches to solving real-world business challenges.
Practical exercises, industry-oriented projects, case studies, and interactive sessions help learners strengthen technical thinking and apply GENAI & MACHINE LEARNING concepts confidently.
Our GENAI & MACHINE LEARNING trainers in London provide personalized mentoring, project support, technical guidance, resume assistance, and career guidance to help learners explore AI opportunities.
Experienced trainers provide industry insights, project knowledge, career guidance, and GENAI & MACHINE LEARNING instruction focused on developing relevant skills for current technology roles.

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS .

Course Syllabus

100% Placements | Get Hired in Top MNC

Career Support

Placement Assistance

Exclusive access to ACTE Job portal

Mock Interview Preparation

1 on 1 Career Mentoring Sessions

Career Oriented Sessions

Resume & LinkedIn Profile Building

We Offer High-Quality Training at The Lowest Prices.

Affordable, Quality Training for Freshers to Launch IT Careers & Land Top Placements.

Call Course Advisor

What Makes ACTE Training Different?

Feature

ACTE Technologies

Other Institutes

Affordable Fees

Competitive Pricing With Flexible Payment Options.

Higher Fees With Limited Payment Options.

Industry Experts

Well Experienced Trainer From a Relevant Field With Practical Training

Theoretical Class With Limited Practical

Updated Syllabus

Updated and Industry-relevant Course Curriculum With Hands-on Learning.

Outdated Curriculum With Limited Practical Training.

Hands-on projects

Real-world Projects With Live Case Studies and Collaboration With Companies.

Basic Projects With Limited Real-world Application.

Certification

Industry-recognized Certifications With Global Validity.

Basic Certifications With Limited Recognition.

Placement Support

Strong Placement Support With Tie-ups With Top Companies and Mock Interviews.

Basic Placement Support

Industry Partnerships

Strong Ties With Top Tech Companies for Internships and Placements

No Partnerships, Limited Opportunities

Batch Size

Small Batch Sizes for Personalized Attention.

Large Batch Sizes With Limited Individual Focus.

LMS Features

Lifetime Access Course video Materials in LMS, Online Interview Practice, upload resumes in Placement Portal.

No LMS Features or Perks.

Training Support

Dedicated Mentors, 24/7 Doubt Resolution, and Personalized Guidance.

Limited Mentor Support and No After-hours Assistance.

Frequently Asked Questions

Looking for better Discount Price?

Call now: +91-7669 100 251 and know the exciting offers available for you!

Does ACTE provide placement?

ACTE provides placement support to students. Please visit our Placed Students List on our website.
We have relationships with top MNCs across different industries.
ACTE conducts development sessions, including mock interviews and presentation skills, to prepare students for interviews.
Our Placement Cell provides career support and placement guidance.
Please visit your Student Portal to access job openings, study materials, videos, recorded sessions, and interview questions.

Can GENAI & MACHINE LEARNING certification from ACTE help with my career?

ACTE certification documents the completion of GENAI & MACHINE LEARNING training and associated learning activities. Its relevance can vary based on employer requirements, practical knowledge, project experience, technical skills, and the position being pursued.

Does the GENAI & MACHINE LEARNING course include practical projects?

Yes, learners work on practical projects involving generative AI applications, large language models, prompt engineering, machine learning algorithms, AI integration, and intelligent application development using relevant tools.

Who conducts the GENAI & MACHINE LEARNING training?

GENAI & MACHINE LEARNING sessions cover artificial intelligence, machine learning, Python, large language models, prompt engineering, AI application development, and model integration through guided learning and practical exercises.

What should I do if I miss a GENAI & MACHINE LEARNING class?

Participants who miss a scheduled class can use available recorded sessions and learning materials to revise missed topics and continue following the GENAI & MACHINE LEARNING course curriculum.

Which training formats are offered for GENAI & MACHINE LEARNING Certification in London?

Learners can choose classroom training, online classes, individual mentoring, fast-track batches, and flexible learning options based on their availability, schedule, and preferred learning method.

Why choose ACTE for GENAI & MACHINE LEARNING Certification in London?

ACTE offers GENAI & MACHINE LEARNING learning with practical projects, guided activities, technical learning, interview preparation, certification assistance, and career-oriented support.

Can I access the course material online?

Yes, available course materials, videos, recorded sessions, and interview preparation resources can be accessed through the Student Portal, subject to the access provided for the course.

Which certificate will I receive after completing the course?

Upon completing the GENAI & MACHINE LEARNING training program, participants may receive an ACTE course completion certificate documenting their training, participation, and acquired skills.

Does the GENAI & MACHINE LEARNING training include practical exercises?

Yes, the training emphasizes hands-on learning through prompt engineering, AI model integration, machine learning exercises, generative AI applications, practical projects, and AI application development scenarios.

What qualifications are required for GENAI & MACHINE LEARNING Certification?

Basic computer knowledge and an interest in artificial intelligence can be helpful. Beginners can also join the course, as learning can start with fundamental concepts and gradually progress to advanced GENAI & MACHINE LEARNING techniques.

How can I access recorded GENAI & MACHINE LEARNING sessions?

After registration, eligible learners can access available recorded classes and study materials through the training platform, allowing them to review GENAI & MACHINE LEARNING lessons at their convenience.

How can I register for GENAI & MACHINE LEARNING Certification in London?

You can register for the GENAI & MACHINE LEARNING Certification in London by completing the registration process and selecting a suitable batch based on your schedule and preferred training format.