By the end of this program, participants will be skilled in data cleaning, performing analysis using various tools, and creating meaningful visualizations to influence business decisions.
Overview of data analytics, its importance in business, and the data analytics workflow.
Explore a dataset and identify potential insights.
Mastering Excel functions, pivot tables, and charts for data analysis.
Create an Excel dashboard to summarize data insights.
Techniques for cleaning and transforming raw data into usable formats.
Clean a dataset by removing duplicates and handling missing values.
Understanding statistical measures, probability, and hypothesis testing.
Perform a t-test to compare two datasets and interpret the results.
Using SQL to query databases and retrieve data for analysis.
Write SQL queries to extract and manipulate data from a database.
Creating effective visualizations using Excel and Power BI to communicate insights.
Design a Power BI dashboard to showcase key business metrics.
Creating visualizations using Python libraries like Matplotlib and Seaborn.
Build data visualizations using Python to represent business data.
Applying analytics to business decision-making processes and understanding KPIs.
Create an analytics report with actionable insights for decision-makers.
Exploring predictive models, regression analysis, and forecasting methods.
Build a linear regression model to predict sales data.
Applying analytics techniques to real-world business problems in marketing, sales, and operations.
Analyze customer data to create a marketing strategy using insights.
Exploring advanced analytics tools like Python, R, and Tableau for deeper insights.
Develop a detailed report using Python for advanced analytics.
Final project to solve a real-world data problem using the techniques learned in the bootcamp.
Present your capstone project and prepare for job interviews in data analytics.
