Boffins Academy

401, Monarch Apartment

IT Park Road, Gayatri Nagar, Nagpur

+91 976 662 5814

24/7 Customer Support

Mon - Sat: 8:00 AM - 8:00 PM

Data Science

Welcome to the frontier of knowledge: Data Science. In our courses, we embark on a journey through the vast landscape of data, where insights are waiting to be unearthed and decisions are guided by the power of analytics. Whether you’re a curious novice or a seasoned professional, our curriculum is crafted to equip you with the tools and techniques to navigate this intricate realm with confidence. From foundational principles to advanced methodologies, we offer a comprehensive exploration of data science, blending theory with practical applications. Join us as we decode the language of data, uncover patterns, and transform information into intelligence. Get ready to embark on a transformative learning experience, where the possibilities are as boundless as the data itself

Module 1: Introduction to Data Science

  • Overview of Data Science
    • Importance and Applications
    • Data Science Process
  • Tools and Technologies
    • Setting Up Development Environment
    • Version Control with Git and GitHub

Module 2: Python Programming for Data Science

  • Introduction to Python
    • Basic Syntax and Data Types
    • Control Structures (if, for, while)
    • Functions and Modules
  • Data Handling with Python
    • NumPy for Numerical Computations
    • Pandas for Data Manipulation
    • Matplotlib and Seaborn for Data Visualization

Module 3: Advanced Python

  • Object-Oriented Programming (OOP)
    • Classes and Objects
    • Inheritance and Polymorphism
  • Advanced Data Handling
    • Working with APIs
    • Data Processing with Itertools and Collections
  • Python for Data Science Libraries
    • Scikit-Learn for Machine Learning
    • Statsmodels for Statistical Analysis

Module 4: SQL for Data Science

  • Introduction to SQL
    • Basic Queries (SELECT, INSERT, UPDATE, DELETE)
    • Joins, Subqueries, and Aggregations
    • Database Design and Normalization
  • Advanced SQL
    • Window Functions
    • Common Table Expressions (CTEs)
    • Performance Optimization

Module 5: Excel for Data Analysis

  • Excel Basics
    • Data Entry and Formatting
    • Formulas and Functions
  • Advanced Excel
    • Pivot Tables and Charts
    • Data Analysis Toolpak
    • VBA Macros for Automation

Module 6: Power BI for Data Visualization

  • Introduction to Power BI
    • Setting Up Power BI
    • Connecting to Data Sources
  • Building Reports and Dashboards
    • Creating Visualizations
    • DAX (Data Analysis Expressions) Basics
  • Advanced Power BI
    • Advanced DAX Functions
    • Power BI Service for Collaboration
    • Custom Visuals

Module 7: Machine Learning (ML)

  • Introduction to Machine Learning
    • Supervised vs. Unsupervised Learning
    • Model Evaluation and Validation
  • Supervised Learning Algorithms
    • Regression (Linear, Polynomial)
    • Classification (Logistic Regression, Decision Trees, SVM)
  • Unsupervised Learning Algorithms
    • Clustering (K-Means, Hierarchical)
    • Dimensionality Reduction (PCA, LDA)
  • Model Deployment
    • Saving and Loading Models
    • Deploying Models with Flask/Django

Module 8: Natural Language Processing (NLP)

  • Introduction to NLP
    • Text Preprocessing (Tokenization, Lemmatization)
    • Feature Extraction (TF-IDF, Word Embeddings)
  • NLP Techniques
    • Sentiment Analysis
    • Named Entity Recognition (NER)
    • Topic Modeling (LDA)
  • Advanced NLP
    • Transformers and BERT
    • Building Chatbots

Module 9: Deep Learning (DL)

  • Introduction to Deep Learning
    • Neural Networks Basics
    • Activation Functions and Optimizers
  • Deep Learning Frameworks
    • TensorFlow Basics
    • Keras for Quick Prototyping
  • Advanced Deep Learning
    • Convolutional Neural Networks (CNNs)
    • Recurrent Neural Networks (RNNs)
    • Generative Adversarial Networks (GANs)

Module 10: Full-Stack Development

  • Front-End Development
    • HTML and CSS Basics
    • JavaScript and Front-End Frameworks (React/Vue)
  • Back-End Development
    • Building RESTful APIs with Django/Flask
    • Database Integration (SQL/MongoDB)
  • Deployment and Cloud
    • Docker and Kubernetes Basics
    • AWS Cloud Services for Deployment
    • CI/CD Pipelines

Module 11: Integrative Project

  • Project Planning
    • Defining Requirements and Scope
    • Designing the Architecture
  • Implementation
    • Data Collection and Preparation
    • Model Training and Evaluation
  • Deployment and Presentation
    • Building a Web Interface
    • Final Deployment and Reporting