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Master Data Science Training
The Data Science Course equips you with end-to-end skills in Python, SQL, Machine Learning, Deep Learning, NLP, and Generative AI. You’ll learn to clean, analyze, and visualize data, build models, and create smart, scalable solutions.
With a hacker’s mindset, the course focuses on real-world problem-solving, ethical data use, and hands-on projects like fraud detection, AI chatbots, and dashboards—making you job-ready for roles in data science and AI.
Master Data Science Course Highlights
The Data Science Course provides end-to-end training in Python, SQL, Power BI, Machine Learning, Deep Learning, NLP, and Generative AI. You’ll master data analysis, visualization, and model building using real-world tools like TensorFlow and PyTorch.
Built with a hacker’s mindset, the course focuses on curiosity, pattern detection, and ethical problem-solving. Through hands-on projects like fraud detection and AI chatbots, you’ll gain practical experience and build a strong portfolio—making you job-ready for roles in data science and AI.
- 70-Hour LIVE Instructor-led Training
- Highly Interactive and Dynamic Sessions
- Practical Training on Latest Tools
- 98% Exam Pass Rate
- Learn from Data Science Trainers
- Career Guidance and Mentorship
- Extended Post-Training Support
Master Data Science Course Learnings
Data Analysis & Visualization: Gain hands-on skills in Python, SQL, Excel, and Power BI to clean, explore, and visualize complex datasets.
Machine Learning & Model Building: Learn to build, evaluate, and deploy ML models for classification, regression, clustering, and predictions.
Deep Learning & Neural Networks: Understand and implement deep learning models using TensorFlow and PyTorch for image and sequence data.
NLP & Generative AI: Work with text data, perform sentiment analysis, and build generative AI tools like chatbots using transformers and OpenAI APIs.
Ethical Problem-Solving with a Hacker’s Mindset: Develop the ability to detect patterns, uncover anomalies, and solve real-world problems with curiosity and ethical data practices.
Master Data Science Course Curriculum
• What is Data Science? Role of a data scientist vs. analyst vs. ethical hacker
• The hacker’s approach to data exploration and problem-solving
• Data lifecycle: collection, preparation, analysis, modeling, deployment
• Real-world applications: cybersecurity, fraud detection, recommendation engines
• Python basics: variables, data types, loops, functions, file I/O
• Introduction to Jupyter Notebooks, Google Colab, Git
• Key libraries: NumPy, Pandas, Matplotlib, Seaborn
• Data handling, filtering, and transformation
Project: Analyze leaked login data for suspicious patterns
• Data cleaning, handling missing values, duplicates, outliers
• Feature engineering, encoding categorical variables
• Scaling and normalization
• Data pipelines for modeling
Project: Clean and prepare a social media dataset for sentiment analysis
• SELECT, WHERE, GROUP BY, JOINs, subqueries
• Aggregations, window functions, and views
• SQL injection basics and security-aware querying
• Data extraction from relational databases
Project: Behavioral analysis from e-commerce transaction logs
• Visualizing data distributions and trends
• Correlation analysis and feature importance
• Matplotlib, Seaborn, and Plotly for hacker-style visuals
• Detecting anomalies and storytelling with data
Project: Identify suspicious patterns in network traffic data
• Descriptive statistics, variance, skewness
• Probability distributions, Bayes’ Theorem
• Hypothesis testing, confidence intervals
• Hacker logic: making data-driven decisions like solving exploits
Project: A/B testing for email campaign performance
• ML process: train-test split, modeling, evaluation
• Regression, classification, clustering
• Decision Trees, KNN, Logistic Regression, Random Forest
• Model performance: accuracy, precision, recall, F1-score
Project: Predict fraud transactions using classification models
• Ensemble techniques: Gradient Boosting, XGBoost
• Feature selection, cross-validation
• Model tuning with GridSearch and RandomSearch
• Model deployment basics with Flask or Streamlit
Project: Customer churn prediction with model tuning
• Text preprocessing: tokenization, stemming, lemmatization
• TF-IDF, Bag of Words, word embeddings (Word2Vec)
• Sentiment analysis, named entity recognition (NER)
• Using SpaCy, NLTK, and Hugging Face transformers
Project: Build a sentiment classifier on Twitter or product review data
• Introduction to neural networks
• Activation functions, backpropagation, optimizers
• CNNs for image data, RNNs for sequence data
• Model building in TensorFlow/Keras and PyTorch
Project: Build a handwriting recognition system (MNIST dataset)
• What is Generative AI? Use cases and ethics
• Introduction to Transformers and LLMs (BERT, GPT)
• Text generation using OpenAI/GPT models
• Image generation with Stable Diffusion/DALL·E
• Prompt engineering and fine-tuning basics
Project: Build an AI-powered chatbot using LLM APIs (e.g., OpenAI GPT)
• Creating dynamic dashboards with Power BI / Tableau
• Python dashboards with Plotly Dash or Streamlit
• Sharing insights in ethical, impactful, and user-friendly ways
Project: Create a business KPI dashboard for live user metrics
Training Package
Designed to get you trained with the core knowledge.- Online Live Training
- Live Projects
- Resume Building
- LinkedIn Grooming
- Mock Interview Sessions
- Certificate Assistance
Job Seeker's Package
Designed to make you job ready with knowledge, experience, and grooming.- Online Live Training
- Live Projects
- Resume Building
- LinkedIn Grooming
- Mock Interview Sessions
- Certificate Assistance
Master Data Science Course Outcomes
Master Data Tools & Languages: Gain strong command over Python, SQL, Excel, Power BI, TensorFlow, and PyTorch to handle data end-to-end.
Build & Deploy ML Models: Learn to create, evaluate, and deploy Machine Learning and Deep Learning models for real-world applications.
Work with Text & Generative AI: Develop skills in NLP, sentiment analysis, and Generative AI using tools like Hugging Face and OpenAI APIs.
Analyze & Visualize Data: Turn raw data into meaningful insights with visual dashboards and clear storytelling for decision-makers.
Think Like a Hacker: Adopt a hacker’s mindset to detect anomalies, solve problems ethically, and handle data with curiosity and precision.
Unlock Career Opportunities in IT
Data Scientist
Design and implement predictive models, analyze trends, and drive data strategies.
Machine Learning Engineer
Build and deploy machine learning systems and AI-powered applications.
Data Analyst
Clean, explore, and visualize data to support business decisions.
Business Intelligence (BI) Analyst
Develop dashboards and reports for executive-level insights.
NLP Engineer
Work on language models, chatbots, and text-based AI systems.
AI Researcher
Innovate in deep learning, generative AI, and advanced algorithms.
Data Engineer
Build scalable pipelines, data warehouses, and infrastructure for large-scale data processing.
Quantitative Analyst (Quant)
Use statistical models in finance, trading, and risk analytics.
Know before you Start
While not mandatory, having basic knowledge of Python or any programming language will help you grasp concepts faster.
You should be comfortable with high school-level math, statistics, and logical reasoning, especially for machine learning and model evaluation.
Like a hacker, you’ll need to explore datasets, ask questions, and uncover hidden patterns. A curious mindset is more valuable than prior expertise.
This is a hands-on course. You'll be working on real-world projects from day one—so consistency and active learning are essential.
You'll work with powerful tools and sensitive data—understanding ethical data use, privacy, and AI responsibility is critical.
Skills You Will Gain
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Real voices, real wins—hear what our learners say!
FAQs
No prior tech background is required. Basic knowledge of math and logical thinking is enough to start. Programming and tools are taught from scratch.
Yes. It’s designed for beginners and upskilled learners alike, with step-by-step modules, real projects, and support at every stage.
Absolutely. You’ll build projects in fraud detection, AI chatbot development, data visualization, and more to showcase your skills.
It’s built with a hacker’s mindset—you’ll learn to explore data deeply, detect patterns and anomalies, and solve problems ethically and creatively.
Yes. You’ll receive a course completion certificate along with guidance to build a professional portfolio and resume.
