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Python programming fundamentals and best practices for data science
Data handling and manipulation using NumPy and Pandas
Data visualization using Matplotlib and Seaborn
Exploratory Data Analysis (EDA) to discover patterns and insights
Data cleaning, handling missing values, and outlier treatment
Statistical concepts including probability, distributions, and hypothesis testing
Feature engineering techniques such as scaling, encoding, and binning
Machine learning algorithms and their practical applications
Model evaluation and performance improvement techniques
Building and deploying machine learning projects using Flask and AWS
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Build responsive and modern user interfaces using HTML, CSS, and React.js
Master JavaScript fundamentals and ES6+ concepts for dynamic web applications
Develop secure and scalable backend APIs using Node.js and Express.js
Design and manage databases with MongoDB, including CRUD operations and data modeling
Connect frontend and backend to create end-to-end full-stack applications
Implement state management, forms, and event handling in React
Understand authentication, middleware, and RESTful API architecture
Build and deploy real-world MERN stack projects with industry best practices
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Analyze and organize data efficiently using Excel formulas, pivot tables, and dashboards.
Write SQL queries to filter, aggregate, and analyze data from relational databases.
Work with real datasets to clean, transform, and prepare data for analysis.
Use Python fundamentals for data analysis and problem solving.
Perform data manipulation using NumPy and Pandas.
Create meaningful data visualizations using Matplotlib and Seaborn.
Build interactive dashboards and reports using Power BI.
Complete industry-oriented projects and build a job-ready analytics portfolio.
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What you'll learn
Learn complete Python fundamentals, including variables, loops, functions, and file handling.
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Build strong programming skills with Object-Oriented Programming (OOPS).
Perform data analysis using industry-standard libraries like NumPy and Pandas.
Create professional charts and graphs using Matplotlib and Seaborn for data visualization.
Develop real-world problem-solving and debugging skills to write clean, efficient code.
