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Diploma in Machine Learning & AI

Join DizitalAdda's Diploma in Machine Learning & AI and master the fundamentals and advanced techniques of building intelligent systems. This 12-month, project-based program offers hands-on training, real-world case studies, and expert mentorship to launch your career in the rapidly evolving fields of AI and ML.

  • Learn from Industry Experts
  • 100% Practical & Project-Based Training
  • Work on Real World Projects
  • Build a Strong, Job-Ready Portfolio

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Let's Discuss What You Want

I want to know what's latest in market

Duration: 12 Months / 288 Hours Mode: Hybrid (Online + Offline) 100% Placement Guarantee Rating: 4.78 ★ (1514 ratings) Level: Beginner Friendly

Key Skills Covered

Python NumPy Pandas Matplotlib Seaborn Plotly Jupyter Notebook Google Colab Git GitHub Supervised Learning Linear Regression Logistic Regression Decision Trees Random Forests SVM KNN XGBoost LightGBM Unsupervised Learning K-Means Hierarchical Clustering DBSCAN Dimensionality Reduction PCA t-SNE Model Evaluation Hyperparameter Tuning TensorFlow Keras PyTorch CNNs RNNs LSTMs GRUs Transfer Learning NLP Text Preprocessing TF-IDF Word Embeddings Transformers BERT GPT NLTK spaCy Hugging Face OpenCV PIL Object Detection Image Segmentation GANs Flask Streamlit Gradio Docker AWS Google Cloud Azure MLflow DVC Linear Algebra Probability Statistics Hypothesis Testing API Integration Web Scraping SQL MongoDB Kaggle Project Management Portfolio Development Resume Building Interview Preparation Presentation Skills Networking

Build Skills That Companies Are Looking For

Our curriculum is designed to match real industry needs, so you're job-ready for roles at companies like TCS, Wipro, Google, and Infosys.

TCS Wipro Google Microsoft Infosys

*Companies mentioned are examples of industry relevance. Logos shown for aspirational and educational purposes only.

Course Modules

Foundation Setup & Python Fundamentals

  • Set up Python environment
  • Learn Python basics
  • Use data structures & algorithms
  • Clean and preprocess data
  • Explore with Python libraries
Python Data Structures Algorithms Data Preprocessing Jupyter Notebook

Data Analysis & Visualization

  • Perform data cleaning
  • Use summary statistics
  • Explore EDA techniques
  • Create visualizations
  • Use Matplotlib & Seaborn
EDA Matplotlib Seaborn Data Cleaning Data Visualization

Machine Learning Fundamentals

  • Apply regression models
  • Use classification algorithms
  • Evaluate model performance
  • Feature engineering basics
  • Train models with Scikit-learn
Machine Learning Regression Classification Model Evaluation Scikit-learn

Advanced Machine Learning

  • Learn ensemble methods
  • Apply SVM classification
  • Use cross-validation
  • Tune hyperparameters
  • Cluster & detect anomalies
Ensemble Methods XGBoost SVM Model Tuning Unsupervised Learning

Deep Learning Foundations

  • Understand neural networks
  • Train CNN models
  • Use RNNs and LSTMs
  • Apply backpropagation
  • Build with TensorFlow & PyTorch
Deep Learning Neural Networks CNN RNN TensorFlow

Natural Language Processing

  • Preprocess and embed text
  • Text classification tasks
  • Sentiment analysis models
  • Use BERT and GPT
  • Build NLP applications
NLP Text Embeddings BERT GPT Chatbots

Computer Vision

  • Image processing tasks
  • Train image classifiers
  • Facial recognition models
  • Use OCR techniques
  • Build with GANs
Computer Vision CNN OCR GANs Image Classification

MLOps & Production Systems

  • Deploy ML models
  • Build CI/CD pipelines
  • Track model versions
  • Monitor production models
  • Scale real-time systems
MLOps CI/CD Model Monitoring Model Deployment Scalability

Specialized Topics & Applications

  • Learn reinforcement learning
  • Use transfer learning
  • Study AI ethics & bias
  • Explore domain use cases
  • Work with AI trends
Reinforcement Learning Transfer Learning AI Ethics Domain Applications Multi-Agent Systems

Industry Projects & Specialization

  • Build industry projects
  • Choose a focus domain
  • Collaborate with mentors
  • Use advanced AI tools
  • Gain practical experience
Industry Projects Specialization Team Collaboration Real-world Tools Capstone Development

Portfolio & Resume Building

  • Build AI/ML portfolio
  • Write project case studies
  • Create standout resume
  • Boost GitHub profile
  • Showcase problem-solving
Portfolio Building Resume Writing GitHub Projects LinkedIn Optimization Technical Storytelling

Placement Preparation & Career Launch

  • Attend mock interviews
  • Practice DS & ML questions
  • Get career coaching
  • Optimize job search
  • Connect with recruiters
Mock Interviews DSA for ML Career Coaching Interview Preparation Placement Support

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What Have We Achieved?

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  • DizitalAdda is a trusted name in tech training, with over 5,000+ successful students and an 85% placement rate. Our hands-on approach and industry-relevant curriculum have helped students land jobs at top companies like Google, Amazon, and Microsoft. We equip learners with the skills needed to excel in the ever-evolving tech world.
  • 1000+ students trained in AI & ML tools : Learners gain hands-on mastery in Python, SQL, Scikit-learn, and TensorFlow — covering EDA, machine learning, deep learning, NLP, and BI tools to build real-world, production-ready models.
  • 80% placed in AI roles : Roles include Prompt Engineer, Generative AI Specialist, and ML Engineer. Projects include building content generators, smart chatbots, and text-based automation systems.

Lets Do a Quick Campus Tour!

What Our Learners Say

"This course was a game-changer. The real projects and mentorship helped me land my first job in AI!"

— Anjali Sharma, GenAI Developer

"Not just theory — we built real GenAI tools! The hands-on approach made learning so much easier."

— Rahul Verma, Prompt Engineer

"I loved the hybrid mode. I could learn remotely and still attend live weekend sessions with mentors."

— Sneha Patel, ML Intern

Frequently Asked Questions

Frequently Asked Questions offers quick answers to common queries, guiding users through features effortlessly.

What is machine learning in AI?

Machine Learning is a subset of AI where systems learn from data and make predictions or decisions without being explicitly programmed.

Is Machine Learning and AI a good career?

Yes, ML and AI are in high demand with strong growth, especially in sectors like healthcare, finance, and automation.

What is the salary of ML and AI?

Salaries range from $95,000 to $150,000+, with senior roles offering even more based on experience and specialization.

Is Machine Learning and AI easy?

It’s challenging and requires strong math and programming, but structured learning and practice make it accessible.

Is ML a high paying job?

Yes, ML is one of the highest paying tech fields with strong demand for roles like Data Scientist and ML Engineer.

Is ML and AI better than CSE?

ML/AI offer niche, high-growth roles while CSE is broader. AI may be better for those targeting intelligent systems.

Is machine learning hard to learn?

It can be complex, but with proper guidance and hands-on practice, it's manageable and highly rewarding.

Is B.Tech in ML good for the future?

Yes, it's one of the best tech choices today with growing relevance across industries.

Is ML in high demand?

Absolutely. AI is being rapidly adopted in every sector, driving up demand for skilled professionals.

What is the salary of B.Tech in Machine Learning?

Graduates earn between $60,000 and $90,000 to start, with potential to exceed $120,000+ in senior roles.

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