Bootcamp description

The  7-Day Data Analytics Bootcamp is designed to equip participants with fundamental skills in data handling, visualization, and analysis. The program begins by introducing data analytics, covering essential concepts such as data types, the lifecycle of data, and basic statistics. Participants will then dive into hands-on exercises focused on data cleaning using Excel and Python, ensuring they are prepared to handle real-world datasets efficiently.

The bootcamp further explores data visualization techniques, teaching participants how to create meaningful charts and conduct exploratory data analysis (EDA) using tools like Excel, Matplotlib, and Seaborn. Additionally, SQL fundamentals are introduced to enable learners to query and manage databases effectively. The machine learning component covers regression and classification models, offering participants the chance to build predictive models using the Scikit-learn library.

On the final day, participants will apply their knowledge in a capstone project, solving a real-world business problem using data cleaning, visualization, and machine learning techniques. The bootcamp concludes with placement training, where learners will receive guidance on resume building, interview preparation, and tips for enhancing employability in the field of data analytics.

What will i learn?

• Data Handling Skills: Ability to collect, clean, and preprocess structured and unstructured data using Excel and Python (Pandas).
• Data Visualization Expertise: Proficiency in creating insightful visualizations and conducting exploratory data analysis (EDA) using Excel, Matplotlib, and Seaborn.
• SQL Querying Proficiency: Competence in writing and executing basic SQL queries for data retrieval, filtering, sorting, and aggregating from databases.
• Machine Learning Foundations: Understanding of machine learning concepts, including building and evaluating basic regression and classification models using Scikit-learn.
• Capstone Project Experience: Hands-on experience applying learned skills to a real-world dataset, solving a business problem through data analysis, visualization, and predictive modeling.
• Job Readiness: Enhanced employability with placement training, including resume building, interview preparation, and practical insights for entering the data analytics field.

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