Artificial Intelligence with Machine Learning Training
Build practical skills in Artificial Intelligence, Machine Learning, Python, data analysis, deep learning, NLP, computer vision, Generative AI, LLMs and model deployment. This is a hands-on training designed around structured learning, practical tasks, projects and AI/ML workflows.
AI & Python Foundations
Learn Python, numerical computing, data handling and the foundations needed for practical AI development.
Machine Learning
Build supervised and unsupervised models, evaluate performance and improve model quality.
Modern AI
Explore deep learning, NLP, LLMs, RAG, AI applications and responsible AI practices.
Performance-Based Stipend
Stipend may be provided on a performance basis, subject to applicable training criteria, work quality and evaluation.
Learn Artificial Intelligence Through Practical Training Work
A structured training for students, freshers and aspiring AI professionals who want practical exposure to data, machine learning, deep learning and modern AI application development.
🧠 What You'll Explore
Understand how AI systems are designed, trained, evaluated and integrated into useful applications.
- ✓Python, NumPy, Pandas and data preparation
- ✓Supervised and unsupervised machine learning
- ✓Model evaluation and optimization
- ✓Deep learning with TensorFlow, Keras and PyTorch
- ✓NLP, embeddings and transformer concepts
- ✓Computer vision and transfer learning
✨ Why Combine AI + Machine Learning?
Modern AI careers increasingly connect classical ML with deep learning and generative AI. This training gives learners a structured path across these areas.
- ✓Generative AI and prompt engineering
- ✓LLM APIs and AI application workflows
- ✓RAG and vector search concepts
- ✓AI agents and tool-use workflows
- ✓Model serving and deployment concepts
- ✓Responsible and ethical AI practices
Build Skills Beyond Textbook Learning
Designed to connect programming, data, machine learning, deep learning and modern AI through practical training activities and portfolio projects.
Python & Data
Work with Python, NumPy, Pandas, data cleaning, analysis and visualization.
Machine Learning
Learn algorithms, feature engineering, validation, metrics and model optimization.
Deep Learning
Explore neural networks, CNNs, transfer learning and practical deep learning workflows.
NLP & LLMs
Understand text processing, embeddings, transformers, LLMs and RAG applications.
Computer Vision
Build image-focused AI solutions using CNNs and pretrained models.
AI Deployment
Explore FastAPI, Streamlit, Docker, model serving, MLOps and monitoring concepts.
56 Modules in Artificial Intelligence with Machine Learning
A structured training curriculum covering Python, data preparation, machine learning, deep learning, NLP, computer vision, Generative AI, LLMs, RAG, deployment and MLOps.
Introduction to Artificial Intelligence
AI concepts, intelligent systems, real-world applications and the AI development lifecycle.
Machine Learning Fundamentals
Supervised, unsupervised and reinforcement learning concepts and workflows.
Python for AI & ML
Python syntax, functions, OOP and practical programming for AI development.
NumPy for Numerical Computing
Arrays, vectorization, broadcasting and numerical operations for machine learning.
Pandas for Data Analysis
DataFrames, filtering, grouping, merging and practical dataset manipulation.
Data Cleaning & Preprocessing
Missing values, duplicates, encoding, scaling and preparing reliable datasets.
Exploratory Data Analysis
Discover patterns, distributions, correlations and insights from real datasets.
Data Visualization
Build informative charts with Matplotlib and visualization best practices.
Statistics for Machine Learning
Probability, distributions, descriptive statistics and statistical reasoning.
Linear Algebra for AI
Vectors, matrices, transformations and concepts used in model computation.
Supervised Learning
Regression and classification workflows using labeled datasets.
Linear & Logistic Regression
Build baseline predictive models and interpret their outputs.
Decision Trees
Tree-based learning, splitting criteria, pruning and interpretability.
Random Forest & Ensembles
Ensemble learning, bagging and robust tree-based prediction.
Gradient Boosting & XGBoost
Boosting concepts and practical high-performance tabular modeling.
Support Vector Machines
Margins, kernels and classification/regression applications.
K-Nearest Neighbors
Distance-based learning, feature scaling and classification.
Naive Bayes
Probabilistic classification and practical text-classification use cases.
Unsupervised Learning
Clustering and pattern discovery without labeled outcomes.
K-Means Clustering
Customer, document and behavioral segmentation with clustering.
Hierarchical Clustering
Agglomerative clustering, dendrograms and cluster interpretation.
PCA & Dimensionality Reduction
Reduce feature dimensions while preserving useful information.
Feature Engineering
Create, transform and select features that improve model performance.
Model Evaluation
Accuracy, precision, recall, F1, ROC-AUC, MAE, MSE and related metrics.
Cross-Validation
Reliable model validation, data splits and avoiding evaluation leakage.
Hyperparameter Tuning
Grid search, randomized search and systematic model optimization.
Overfitting & Regularization
Bias-variance trade-offs, L1/L2 regularization and generalization.
Machine Learning Pipelines
Build repeatable preprocessing, training and evaluation pipelines.
Deep Learning Fundamentals
Neurons, layers, activation functions, loss and backpropagation.
TensorFlow & Keras
Create, train and evaluate neural networks using TensorFlow/Keras.
PyTorch Fundamentals
Tensors, datasets, models and training loops with PyTorch.
Neural Network Optimization
Optimizers, learning rates, batching, callbacks and training strategy.
Convolutional Neural Networks
CNN architecture and image feature learning.
Transfer Learning
Reuse pretrained models for practical computer vision tasks.
Computer Vision
Image preprocessing, classification and basic vision application workflows.
Natural Language Processing
Text preprocessing, tokenization and language-processing foundations.
Text Classification
Build practical classifiers for sentiment, topics and document categories.
Embeddings & Semantic Search
Represent text as vectors and compare semantic similarity.
Transformers Fundamentals
Attention, transformer architecture and modern language models.
Generative AI Fundamentals
LLMs, generative models, prompting and responsible AI concepts.
Prompt Engineering
Design, test and evaluate prompts for AI-assisted workflows.
LLM APIs & AI Applications
Integrate language models into practical Python applications.
RAG Fundamentals
Retrieval-augmented generation, documents, embeddings and grounded responses.
Vector Databases
Store and search embeddings for semantic retrieval workflows.
AI Agents & Tool Use
Build AI workflows that reason over tasks and interact with tools.
Model Explainability
Understand feature importance, interpretability and transparent ML decisions.
Responsible & Ethical AI
Bias, fairness, privacy, safety, transparency and responsible model use.
MLflow & Experiment Tracking
Track experiments, parameters, metrics and model versions.
FastAPI for Model Serving
Expose trained models through practical REST APIs.
Streamlit AI Applications
Create interactive AI/ML demos and portfolio applications.
Docker for AI Applications
Containerize AI applications and reproducible model environments.
Cloud AI Deployment Concepts
Understand deployment patterns for AI/ML workloads in cloud environments.
MLOps Fundamentals
Connect data, training, evaluation, deployment and monitoring into a lifecycle.
AI Model Monitoring
Monitor model behavior, drift, performance and operational health.
AI Project Presentation & Portfolio
Document technical decisions, prepare a project walkthrough and organize an AI portfolio.
Final AI + ML Capstone
Build, document and present an end-to-end intelligent application.
Build Projects You Can Discuss in Interviews
Apply AI and machine learning concepts through structured training projects designed to strengthen your portfolio and practical understanding.
🧠 AI Prediction System
Build an end-to-end supervised machine learning solution from dataset preparation to model evaluation.
📊 Customer Segmentation
Use clustering and visualization to identify meaningful customer or user groups.
💬 NLP Sentiment Analyzer
Create an NLP system that classifies text sentiment and presents results in an interactive interface.
👁️ Image Classification App
Train or fine-tune a CNN/transfer-learning model and expose predictions through an application.
🤖 AI Chatbot with RAG
Build a knowledge-grounded chatbot using embeddings, retrieval and an LLM workflow.
🚀 Deployable AI Application
Package an AI model as an API/application using FastAPI, Docker and deployment-ready practices.
Complete Your Training With Career Documentation
On successful completion of the training requirements, eligible interns can receive applicable training documentation and completion credentials.
Get Your Industry-Recognized Certificate
Successfully complete your Artificial Intelligence with Machine Learning Training and receive a professional training certificate from LetsIntern to showcase your practical learning, project experience and AI/ML skills.
Artificial Intelligence with Machine Learning Training Certificate — sample certificate displayed above.
*Additional recommendations or documents are subject to eligibility and completion criteria.
Skills You Can Build for AI & Machine Learning Careers
The training is designed to help you build practical foundations relevant to entry-level AI, ML, data and applied AI roles.
🤖 AI Engineer
Build intelligent applications, automation workflows and AI-powered features.
🧠 Machine Learning Engineer
Develop, evaluate and improve predictive and machine learning systems.
📊 Data Scientist
Use data, statistics and machine learning to solve business and analytical problems.
💬 NLP / LLM Engineer
Work on language models, NLP, embeddings, RAG and conversational AI.
👁️ Computer Vision Engineer
Develop image-based machine learning and deep learning applications.
⚙️ MLOps Engineer
Support model deployment, experiment tracking, monitoring and ML lifecycle automation.
What Interns Can Say About the Experience
“The training helped me understand the complete ML workflow—from cleaning a dataset to evaluating a model. The project work made the concepts much easier to discuss in interviews.”
Shikha Verma — Placed in Mircrosoft“I liked the combination of Python, machine learning and practical AI applications. Building projects gave me something concrete to show in my portfolio.”
Ananya Sharma — Placed at TCS“The AI and ML modules gave me a structured path instead of jumping randomly between tools. The capstone was especially useful for practicing an end-to-end workflow.”
Rohan Verma — Placed at Infosys“The training gave me hands-on exposure to model training, NLP and deployment concepts. I found the project-based format useful for building confidence.”
Priya Singh — Placed at Accenture“I wanted practical AI experience beyond tutorials. The curriculum covered classical ML as well as modern LLM and RAG concepts, which was valuable for my portfolio.”
Ethan Williams — Placed at Microsoft“Working through an AI project from preprocessing to deployment helped me connect the theory with how an actual application can be built.”
Olivia Johnson — Placed at IBMWhat Students Can Gain From the AI & ML Training
📚 Structured Learning
- ✓Step-by-step AI and ML curriculum
- ✓Practical assignments and project work
- ✓Exposure to current AI development workflows
- ✓Portfolio-oriented deliverables
💼 Career Preparation
- ✓Project experience for your resume
- ✓Practical AI/ML terminology and workflows
- ✓Experience discussing technical projects
- ✓Performance evaluation during training activities
Start Your Artificial Intelligence with Machine Learning Training
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Training Registration Form
Register for the Artificial Intelligence with Machine Learning Training. Complete the form carefully and provide accurate information.
💰 Stipend may be provided on a performance basis and is subject to eligibility, work quality, participation and evaluation. Stipend is not guaranteed for every intern.
💰 Performance-Based Stipend
Eligible interns may be considered for a stipend based on performance. Stipend eligibility and amount, where applicable, depend on training requirements, quality of work, task completion, participation, consistency and performance evaluation. Stipend is performance-based and is not guaranteed for every intern.
Secure Your AI & Machine Learning Training Registration
Apply Before Today's Deadline
Training Registration Form
Artificial Intelligence with Machine Learning Training — submit your details to begin the registration process.
Your AI Career Can Start With a Real Training.
Learn, build, practice and create portfolio-ready AI and machine learning projects through a structured training experience.
Enroll for AI & ML Training →Training – Stipend Provided
📅 Phase 1: Initial 15-Day Training & Onboarding
You will start with a focused 15-day training period, guided by experienced mentors and our support team.
This phase helps you build core Full Stack Web Development + AI skills, required to work on real client projects.
🚀 Phase 2: Paid Client Project Work (Stipend Starts)
After successful completion of training, you will be assigned to AI-powered live client projects.
✔ From this stage, stipend will be provided
✔ Stipend is performance-based and task-driven
💵 Stipend Range:
₹10,000 – ₹16,000 per month
(Based on project complexity, task completion, and performance evaluation)
🏦 Stipend Payment & Management
Our Accounts & Support Team ensures smooth and timely stipend processing.
You will be asked to submit your bank or UPI details once you become eligible for stipend payouts.
This AI Machine Learning Training helps students build strong foundations in artificial intelligence, machine learning algorithms, and real-world AI applications.
By enrolling in our AI Machine Learning Training, students gain practical exposure to model training, data preprocessing, and deployment techniques.
Training (HOW IT WORKS – SIMPLE FLOW)
Step 1:
15-Day Structured Training & Onboarding
(Learn Python, Machine Learning fundamentals, Data Handling & AI basics)
Step 2:
Work on Live AI & ML Projects
(Hands-on projects in Machine Learning, NLP, Computer Vision & Predictive Models)
Step 3:
Performance Review → Stipend Eligibility
(Stipend based on project completion, model accuracy & performance)
Step 4:
Training Certificate + LOR + Career Support
(Verified certificate, Letter of Recommendation & AI/ML career guidance)
AI & Machine Learning Intern – Responsibilities
Learn & Implement Machine Learning & AI fundamentals
Work on AI/ML projects (prediction, classification, NLP basics)
Train and test ML models
Analyze model performance & accuracy
Collaborate with mentors on AI project tasks
Maintain code and project documentation
Present project outcomes during reviews
Trusted by 5000+ Students Across India
Real experiences from our training students
Testimonials
Trusted by Thousand of Students and Tutors
Ananya Sharma – Placed at Infosys
Rahul Nair – Placed at TCS
Priya Reddy – Placed at Wipro
John Williams (Nigeria) – Placed at Microsoft
Duration: Choose Your Training Length —
1, 2, 3, 4, 5, or 6 Months (Online & Remote)
Stipend Given – Check Training Overview
REGISTRATION FORM
Fill up the Below form to get registered in the program
Tech Stack & AI Tools Covered
Unlock These Skills During the Program
Core AI & Machine Learning:
Python Programming (Numpy, Pandas, Scikit-learn, Matplotlib)
Supervised & Unsupervised Learning
Model Training, Testing & Evaluation
Regression, Classification, Clustering, and Dimensionality Reduction
Deep Learning & Neural Networks:
TensorFlow & Keras or PyTorch
CNNs, RNNs, LSTMs
Image Classification, Object Detection, Sentiment Analysis
NLP & Generative AI:
Text Preprocessing, Tokenization, Embeddings
Transformers, BERT, GPT models
Chatbots, Text Summarization, AI Writing Tools
Data Handling & Visualization:
Data Cleaning, Feature Engineering
Exploratory Data Analysis (EDA)
Data Visualization with Seaborn, Matplotlib, Plotly
Databases & Data Storage:
SQL for structured data
MongoDB for unstructured data
Cloud Storage basics (Google Drive, Firebase, AWS S3)
Tools & Technologies:
Jupyter Notebook, Google Colab
VS Code for script-based development
APIs (OpenAI, Hugging Face, etc.)
Deployment & Hosting:
Streamlit / Flask for app deployment
Hugging Face Spaces, Vercel, or Render
Intro to MLOps and model versioning
Real-World Project Experience:
Build real AI solutions like chatbots, image classifiers, and content generators
Work on client-based or simulated industry projects
Training Project Roadmap:
Full Stack Web Developer Training with Major, Minor, and Practice Projects:
Trusted Collaborators
Why You Need This Training
🔥 Don't just prepare for a job. Prepare for a future. Enroll Now! 🔥
1. The Job Market is Brutal — Skills Beat Degrees
Today, a degree alone isn’t enough. Companies hire those who can build real-world projects, not just write exams. This training teaches you exactly what the industry demands, making you job-ready — not just book-smart.
2. You’re Stuck in “Tutorial Hell” — It’s Time to Break Free
Watching endless YouTube videos and following tutorials won’t make you a real developer. Here, you’ll build real projects, work like a real developer, and finally feel confident to face interviews and clients.
3. Confidence Comes From Action — Not Just Learning
Most students fear interviews because they haven’t actually applied their knowledge. This training gives you hands-on experience, teamwork exposure, and the chance to build a portfolio that speaks louder than your resume.
4. Learn Smart, Not Hard — Focused Curriculum, Zero Wastage
No more wasting time on outdated topics. Our program is laser-focused on the exact skills tech companies demand in 2025 — React, Node.js, MongoDB, GitHub, APIs, Hosting — everything you truly need to succeed.
5. Real-World Projects — Proof of Your Talent
Employers don’t care what courses you attended; they care what you can build. This training lets you build apps, deploy websites, and showcase your skills with pride.
6. You Deserve a Career, Not Just a Job
You’ve worked hard. You deserve more than rejections and unpaid trainings. With the right skills, you can start your career strong, earn respect, and stand out — no matter your background.
7.Graduating Isn’t Enough Anymore — Skills Are the New Degree
In today’s competitive world, only those who can prove their skills survive. This training transforms you from just another graduate into a true developer.
8.Learn How Real Developers Work
Textbook knowledge won’t teach you teamwork, client handling, deadlines, and real-world problem-solving. Here, you work on real projects, with real deadlines, in a real remote environment.
Eligibility Criteria
Open to all graduates, final-year students, freshers, and working professionals.
No previous experience is required as full guidance and mentorship are provided.
Watch a Live Artificial Intelligence with Machine Learning Training Session below !
Duration: Choose Your Training Length —
ENROLLMENT FORM
Fill the form below to get enrolled in the program 👇🏻
Meet our Ex-Interns
Ayush Parasha- Student at Arya College of Engineering and IT
Pranav Joshi- Full Stack Developer
RITU SINGH-FullStack Developer
Jahruddeen Ansari-DevOps Engineer | AWS Practitioner Certification – Associate
Syed Kashif- New Delhi
Jonal Suthar – TCS | Systems Engineer
PRATIBHA KUMARI-RAMS Engineer @ Alstom
Ramavath Harish-NIT MEGHALAYA
Rahul Bansal – Product Manager at HP India
krishnavamshi Thadooru-Mern Full Stack Developer
Shubhanshu roy-MVJ College of Engineering, Bangalore, India
Deepthi Muthineni-Project Engineer at Wipro
Ayushi mallawat – Full Stack Web developer Intern at Solar Secure Solutions (Part of CWS)
Mayank Parmar-Intern at Solar Secure Solutions | Web developer| SVNIT (Part of CWS)
Ritesh Shukla- Full stack developer Intern at Soalr secure solutions(Part of CWS)
Mohit Kapil- IIT Roorkee’23 | Frontend Developer
Mritunjay Mishra-Software Developer | Java | Python
Rachin-Associate QA Engineer at Empyra software solutions
Shivesh Singh – Software Engineering Student | AI/ML Enthusiast
Junaid Aftab – Full Stack Developer | Recruiter
Ayush Kumar – Computer Science Student | Learner | Generative AI
Sheebamol TG-Web developer/WordPress Developer
Uday Dalvi-Java/ web dev/ SQL developer
Saipranav Sapare-Front-End intern at Solar Secure Solutions (A part of CWS)
Testimonals
Some Top recruiters...
FAQs
To begin, complete the registration form above by entering your name, email ID, and mobile number. Mention if you’re a student or a professional, along with your college or workplace details. You can also pick a convenient start date, and we’ll try our best to match it.
📩 Offer Letter: After we verify your registration, your offer letter will be issued and sent to your email within a few hours or the next morning.
📩 Welcome Package: On your chosen start date, you’ll receive login credentials and step-by-step guidance via email.
In case you have any queries, you can reach out through hr@corporatewebsolutions.in or WhatsApp/call +91-7618025090.
Definitely! Our support team assists with college-required documents such as attendance sheets, evaluation reports, progress updates, and project summaries throughout your program.
If you need to take a leave for any reason, simply email us or drop a WhatsApp message. You don’t have to wait for a response — just inform us and focus on your priority. Once you’re ready, you can easily resume your tasks.
Yes, a laptop or desktop with a good internet connection is mandatory for participating in this program.
Our programs feature pre-recorded video sessions and LIVE sessions both (Hybrid ) to offer maximum flexibility. Everyone — students, professionals, and mentors — can learn at their own pace without schedule conflicts.
Don’t worry there is an AI-powered assistant to help you with all your coding-related queries. Andie can check and debug code, generate new code, and even build entire projects for you.
This feature is exclusively available to registered candidates through their Task Portal.
Since mentors cannot be available 24/7, Andie was developed to bridge the gap. Located at the bottom-left corner of every module, this Full Stack Developer Bot is capable of writing, reviewing, and troubleshooting code anytime, ensuring you get instant solutions to your coding challenges, day or night.
This training cum training opportunity is designed in such a way as from fresher to a professional anyone can get benefit out of it, The opportunity is divided into 15+ modules, and every Module contains 15-20 small tasks plus 1 project (in the last) based upon what you have learnt in that particular module. The complexity and practicality of your modules and projects will gradually increase, Timing is flexible, schedule yours accordingly. After completing every project given in the modules, Submit within the deadlines.
A major part of this program contains a training part, however we have many projects (2 Major, 15 Minor and many practice projects) and many internal and external resources to sharpen the skills of the candidates. It is a self paced program, Training and trainings will go simultaneously. After every Module, there will be a project related to it (may it be a minor, major or practice project)
We have 20+ projects to provide hands on Experience and sharpen the skills of the Interns.
About Paid Projects_
Paid projects will be provided to the interns on two basis
1) The assignments/projects, which all students sends goes directly to our USA team. they evaluate all of them and create a kind of ranking sheet based upon some factors like quality, accuracy, deadline met etc. They keep this list with them for future paid projects.
2) The availability and number of the projects available.
The training is split into 15+ modules, each with 15–20 tasks and one project. As you progress, the complexity grows to ensure steady skill development. Projects must be submitted on time, and you can plan your schedule flexibly.
You’ll work on over 20 projects to build real-world experience.
👉 Paid Project Opportunity: Based on your performance (quality, speed, and accuracy), you may be eligible for paid tasks offered by our USA team, subject to availability.
Anyone interested can join! Basic knowledge of HTML, CSS, or JavaScript is a bonus but not compulsory. Graduates from any stream are welcome. There are no restrictions based on nationality, age, or background.
You decide your working hours! Whether you’re a student or a working professional, you can complete modules at your convenience. Plus, the training is 100% remote — work from wherever you are most comfortable.
Once enrolled, you’ll have lifetime access to all training content, unless there’s a policy change in the future.
Absolutely! You’ll receive full training material, video tutorials, and 24/7 coding assistance before and during your project work.
Yes, but it depends! Stipends are offered based on your performance, the nature of the project, and USA team evaluations. Stipends typically range from ₹8,000 to ₹18,000 INR ($99 – $219) or higher, depending on project availability.
We actively hire top-performing interns for internal and client roles based on project availability. Additionally, we regularly post openings from our partners so you can apply even after completing the program.
Your certificate will be automatically prepared and scheduled to be emailed around your program completion date. Allow up to 48 extra hours if it falls on a weekend or holiday.
LORs are awarded to exceptional candidates based on strict performance criteria. If you require a LOR for special circumstances like studying abroad, you may also directly request it from HR.
Of course! Although not mandatory, if you find the program valuable, feel free to refer it to friends, classmates, or colleagues who might benefit.
Duration: Choose Your Training Length —
1, 2, 3, 4, 5, or 6 Months (Online & Remote)
Stipend Given – Check Training Overview
REGISTRATION FORM
Fill up the Below form to get registered in the program
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