Data Science And Machine Learning With Gen AI
Master the Future with Data Science, Machine Learning & Generative AI.Step into the world of data-driven innovation with our industry-focused program. From Python basics to advanced ML models and Gen AI tools, you’ll gain the expertise to analyze data, build intelligent systems, and create AI-powered solutions that transform businesses. With hands-on projects, real case studies, and expert mentorship, this course equips you to launch a high-growth career in AI, Data Science, and next-gen technologies.
7 Month
.Duration
Virtual Live
Classes
100% Job
Assurance
Languages
English | Hindi
Get Certifications From
Course Highlights
Industry Mentorship
Learn directly from top Data Scientists & AI Engineers
Job-Ready Skills
Resume building, interview prep & 100% job assurance
Capstone Project
End-to-end real-world AI/ML solution with Gen AI integration
Gen AI Mastery
Gain hands-on expertise with cutting-edge Generative AI tools like ChatGPT, GPT-4, and DALL·E.
Master these Tools
Skills Covered
Core Machine Learning
.
Deep Learning Expertise
.
Natural Language Processing
.
Cloud AI Services
.
Generative AI Applications
.
Data Analysis & Visualization
.
Course Curriculum
Learn everything from data analysis and machine learning to deep learning, NLP, and big data. Build hands-on projects, master tools like Python, TensorFlow, and Hugging Face, and gain job-ready skills to succeed in today’s AI-driven world.
Module 1: Introduction to Data Science & AI
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What is Data Science, Machine Learning & Generative AI
Real-world applications of AI across industries
Career opportunities & roadmap in Data Science
Module 2: Python Programming for Data Science
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Python fundamentals: variables, loops, functions
Working with NumPy & Pandas for data handling
Data visualization with Matplotlib
Using Jupyter Notebook effectively
Version control basics with Git & GitHub
Module 3: Data Handling & Preprocessing
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Importing & collecting data from multiple sources
Cleaning & transforming datasets
Handling missing values & outliers
Feature scaling & normalization
Encoding categorical variables
Module 4: Data Visualization & Analytics
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Exploratory Data Analysis (EDA)
Visualizing trends with Matplotlib & Seaborn
Interactive dashboards with Plotly
BI tools: Tableau & Power BI basics
Data storytelling techniques
Module 5: Statistics & Probability for AI
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Descriptive vs inferential statistics
Probability distributions & random variables
Hypothesis testing & confidence intervals
Correlation & regression analysis
Statistical significance in ML models
Module 6: Machine Learning Fundamentals
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Types of ML: supervised, unsupervised, reinforcement
Regression models: linear & logistic regression
Classification models: KNN, Decision Trees
Clustering algorithms: K-Means, Hierarchical
Model evaluation metrics (accuracy, precision, recall, F1)
Module 7: Advanced Machine Learning
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Ensemble methods: Bagging, Boosting, Stacking
Random Forest, XGBoost, LightGBM
Feature engineering & selection
Dimensionality reduction: PCA, LDA
Hyperparameter tuning with GridSearch & RandomSearch
Module 8: Deep Learning with Neural Networks
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Fundamentals of Neural Networks
Activation functions & optimizers
Building ANN using TensorFlow & PyTorch
Dropout & regularization techniques
Backpropagation & training deep networks
Module 9: Computer Vision with AI
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Image preprocessing & augmentation
CNN architecture for image recognition
Transfer learning with VGG, ResNet, Inception
Object detection using YOLO & SSD
Real-world projects: face detection, OCR
Module 10: Natural Language Processing (NLP)
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Text preprocessing: tokenization, stemming, lemmatization
Bag of Words & TF-IDF techniques
Word embeddings: Word2Vec, GloVe, FastText
Sentiment analysis with ML models
Sequence models: RNN, LSTM, GRU
Module 11: Generative AI Fundamentals
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Transformer architecture explained
Attention mechanism & self-attention
BERT, GPT, LLaMA model overview
Fine-tuning Large Language Models with Hugging Face
Prompt engineering basics
Module 12: Applied Generative AI Projects
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Building AI-powered chatbots with LLMs
Text summarization & QnA systems
Text-to-image models: Stable Diffusion, DALL·E
Code generation with Gen AI
Deploying generative models using APIs
Module 13: Big Data & Analytics
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Introduction to Hadoop & HDFS
Apache Spark basics for data processing
ETL pipelines in data science
Real-time analytics with Apache Kafka
Spark MLlib for large-scale ML
Module 14: Cloud Computing for AI
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Introduction to AWS, Azure, and GCP
Cloud storage & compute services
Deploying ML models on cloud
Serverless computing with AWS Lambda
Cloud-based AI APIs
Module 15: Responsible & Ethical AI
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Understanding AI bias & fairness
Explainable AI (XAI) techniques
Data privacy regulations: GDPR, HIPAA
Responsible AI practices in real-world
Building transparent AI systems
Module 16: Domain-Specific AI Applications
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AI in healthcare: diagnostics, drug discovery
AI in finance: fraud detection, risk modeling
AI in e-commerce: recommendation systems
AI in business automation & supply chain
AI in social media & marketing
Module 17: Advanced Topics in AI & M
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Reinforcement learning basics
Q-learning & deep Q-networks (DQN)
Graph neural networks (GNNs)
Time series forecasting: ARIMA, Prophet, LSTM
Edge AI & IoT-based AI applications
Module 18: Capstone Project & Portfolio Building
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End-to-end AI/ML project lifecycle
Using real-world datasets for projects
Deployment of AI models in production
Building & publishing portfolio on GitHub
Presenting case studies for interviews
Module 19: Career Preparation & Job Readiness
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Resume & LinkedIn optimization for AI/DS roles
Preparing for technical interviews
Mock interviews with experts
Freelancing & global job opportunities
Building personal brand in AI/ML
About Data Science And Machine Learning With GenAI Course
Our Data Science & Machine Learning with Generative AI Program is designed to equip you with the skills needed to analyze data, build predictive models, and create cutting-edge AI applications. You’ll master Python, statistics, machine learning, deep learning, NLP, computer vision, and Generative AI—empowering you to solve real-world problems, accelerate your career, or kickstart your freelancing journey.
✅ Practical, Project-Based Learning
Through hands-on labs, live projects, Kaggle-style challenges, and capstone assignments, you’ll gain practical experience in data preprocessing, model training, and deploying AI/ML solutions. By the end, you’ll have a strong portfolio showcasing your expertise in AI and ML, making you job-ready for high-demand roles.
✅ Expert Mentorship & Career Support
Learn directly from industry experts, receive personalized career guidance, prepare for top interviews, and get assistance for certifications in Data Science & AI. Plus, earn a recognized certification to stand out to employers and clients in the competitive AI/ML job market.
✅ For Everyone Ready to Master AI & Data Science
Whether you’re a student, IT professional, or entrepreneur, this program will help you master data-driven decision-making, machine learning, and Generative AI—preparing you for the future of intelligent systems and scalable AI solutions.
👥 Who Should Enroll?
✔ Students & graduates aiming to start a career in Data Science, ML, or AI
✔ Working professionals looking to upskill or switch into Data/AI roles
✔ Entrepreneurs & innovators wanting to integrate AI into their products & services
Career Opportunities After the Course
List potential roles students can pursue after completing the course, such as
- Data Scientist
- Generative AI Enginee
- AI Research Scientist
- Data Analyst / Business Analyst
- Computer Vision Engineer
- NLP Engineer
- Machine Learning Engineer
With 100% job assurance, our course prepares you for a lucrative career in Data Science.
Authorised Training Partners
Live Virtual Classes
₹9999
EMI Options Available
Batch Timings
📅 Weekdays: 7 PM – 9 PM
📅 Weekends: 10 AM – 12 PM.
⭐ Intensive interview preparation.
⭐ Real-life interview case study.
Total Course Duration : 6 Months
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