namate24training.academy
Data Science Career Track: From Novice to Analyst.
This immersive program is designed to take you from the basics of data analysis to building predictive machine learning models, equipping you with the skills needed for a career in data science.
Who can attend: Aspiring data scientists, career changers from analytical fields (like finance or marketing), software developers looking to specialize, and recent graduates from STEM fields.
Prerequisites: Strong logical and problem-solving skills. A solid foundation in high school-level mathematics is essential. Prior programming experience is helpful but not required.
Duration: 12 Weeks (Approximately 8-10 hours of study per week).
Learning Outcomes: Upon completion, you will be able to:
Use Python and its core libraries (Pandas, NumPy, Matplotlib) for data analysis.
Clean, process, and manipulate large datasets to prepare them for analysis.
Create insightful data visualizations to communicate findings effectively.
Understand and apply fundamental statistical concepts to data.
Build and evaluate foundational machine learning models for classification and regression.
Complete and present a portfolio-worthy capstone project.
Course Modules
Module 1: Python for Data Science Foundations (Weeks 1-2)
Lesson 1.1: Introduction to the Data Science Workflow.
Lesson 1.2: Python Programming Fundamentals (Variables, Data Types, Control Flow).
Lesson 1.3: Data Manipulation with NumPy for numerical operations.
Lesson 1.4: Data Wrangling and Analysis with Pandas.
Module 2: Data Visualization & Storytelling (Weeks 3-4)
Lesson 2.1: Principles of effective data visualization.
Lesson 2.2: Creating static plots with Matplotlib.
Lesson 2.3: Building beautiful statistical graphics with Seaborn.
Lesson 2.4: Project: Create an exploratory data analysis (EDA) dashboard.
Module 3: Machine Learning Fundamentals (Weeks 5-8)
Lesson 3.1: Core Concepts: Supervised vs. Unsupervised Learning.
Lesson 3.2: Linear Regression for predicting continuous values.
Lesson 3.3: Logistic Regression for classification tasks.
Lesson 3.4: Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score).
Lesson 3.5: Introduction to more advanced models like Decision Trees.
Module 4: Capstone Project (Weeks 9-12)
Lesson 4.1: Project Scoping and Dataset Selection.
Lesson 4.2: In-depth Analysis, Model Building, and Fine-tuning.
Lesson 4.3: Communicating Your Results.
Lesson 4.4: Final Project Presentation and Portfolio Building.
Full-Stack Web Development Bootcamp
This comprehensive bootcamp covers everything you need to build and deploy modern, dynamic web applications, from the user-facing front-end to the server-side back-end.
Who can attend: Aspiring web developers, entrepreneurs wanting to build their own products, graphic designers looking to code, and anyone wanting to build a career in software engineering.
Prerequisites: None! This course is designed for beginners. You just need determination and strong problem-solving skills.
Duration: 14 Weeks (Approximately 10-12 hours of study per week).
Learning Outcomes: Upon completion, you will be able to:
Build responsive and interactive user interfaces using HTML, CSS, and JavaScript.
Develop complex client-side applications with a modern framework like React.
Create robust server-side applications and APIs using Node.js and Express.
Design and manage databases using both SQL (PostgreSQL) and NoSQL (MongoDB).
Use Git and GitHub for version control and collaboration.
Deploy a complete full-stack application to the web.
Course Modules
Module 1: Front-End Foundations (Weeks 1-4)
Lesson 1.1: The Anatomy of the Web (HTTP, Browsers, Servers).
Lesson 1.2: Structuring Content with HTML5.
Lesson 1.3: Styling with CSS3, including Flexbox and Grid.
Lesson 1.4: Core Programming with JavaScript (ES6+).
Module 2: Modern Front-End with React (Weeks 5-7)
Lesson 2.1: Thinking in Components.
Lesson 2.2: State and Props Management.
Lesson 2.3: Handling Events and Forms.
Lesson 2.4: Interacting with APIs (Fetching Data).
Module 3: Back-End Development with Node.js (Weeks 8-10)
Lesson 3.1: Introduction to Node.js and the npm ecosystem.
Lesson 3.2: Building a Server with Express.js.
Lesson 3.3: Designing and Building RESTful APIs.
Lesson 3.4: Authentication and Security fundamentals.
Module 4: Databases and Deployment (Weeks 11-14)
Lesson 4.1: Working with a PostgreSQL (SQL) database.
Lesson 4.2: Introduction to MongoDB (NoSQL).
Lesson 4.3: Version Control with Git and GitHub.
Lesson 4.4: Deployment and Full-Stack Capstone Project.
Programming Languages: Python for All
This course focuses on mastering one of the world's most popular and versatile programming languages: Python. It's designed for absolute beginners and will provide a strong foundation for any programming-related career path.
Who can attend: Absolute beginners with no coding experience, students, professionals looking to automate tasks (in finance, marketing, etc.), and those wanting a solid foundation before diving into Data Science or Web Development.
Prerequisites: None. This is a true beginner's course.
Duration: 8 Weeks (Approximately 5-7 hours of study per week).
Learning Outcomes: Upon completion, you will be able to:
Write clean, efficient, and readable Python code.
Understand and apply core programming concepts like variables, loops, and functions.
Work with Python's fundamental data structures (lists, dictionaries, sets, tuples).
Grasp the principles of Object-Oriented Programming (OOP).
Read from and write to files on your computer.
Install and use third-party libraries to extend Python's functionality.
Build a complete command-line application as a final project.
Course Modules
Module 1: Programming Fundamentals (Weeks 1-2)
Lesson 1.1: Your First Program ("Hello, World!").
Lesson 1.2: Variables and Core Data Types (Integers, Floats, Strings, Booleans).
Lesson 1.3: Taking User Input.
Lesson 1.4: Control Flow with Conditional Statements (if, elif, else) and Loops (for, while).
Module 2: Data Structures and Functions (Weeks 3-4)
Lesson 2.1: Organizing Data with Lists and Tuples.
Lesson 2.2: Key-Value Pairs with Dictionaries.
Lesson 2.3: Writing Reusable Code with Functions.
Lesson 2.4: Understanding Scope and Arguments.
Module 3: Object-Oriented Programming (OOP) (Weeks 5-6)
Lesson 3.1: Introduction to OOP: Thinking in Objects.
Lesson 3.2: Creating Classes and Objects.
Lesson 3.3: Understanding Methods and Attributes.
Lesson 3.4: Principles of Inheritance.
Module 4: Advanced Concepts & Final Project (Weeks 7-8)
Lesson 4.1: Handling Errors with Exception Handling (try/except).
Lesson 4.2: Working with Files (Reading and Writing Text Files).
Lesson 4.3: Introduction to the Python Standard Library and pip.
Lesson 4.4: Final Project: Build a practical application like a contact book or a simple budget tracker.
Connect
Empowering teachers and students worldwide, together.
Support
Learn
training@namate24academy.com
+916364224826
© 2025. All rights reserved.