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Course Details

Data Analytics with Python

Course Type : Online

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Data Analytics Course Outline

Module 1: Introduction to Data Analytics

What is Data Analytics and why is it important?
Roles and responsibilities of a Data Analyst.
Types of data (numerical, textual, time-based).
Data analysis process (gathering, cleaning, analyzing).

Module 2: Proficiency in Excel/Google Sheets

Basic features of Excel (formulas, functions, pivot tables).
Data cleaning (removing duplicates, handling missing data).
Visualization (charts, graphs).
Advanced features (Macros, VBA).

Module 3: SQL Database Management

Basics of relational databases and SQL.
Data retrieval (SELECT, WHERE, JOIN, GROUP BY, ORDER BY).
Data update and manipulation (INSERT, UPDATE, DELETE).
Case study: Data analysis from a database.

Module 4: Programming for Data Analysis (Python/R)

Python basics (loops, conditional statements).
Libraries:
NumPy: Matrix and mathematical analysis.
Pandas: Data manipulation.
Matplotlib and Seaborn: Data visualization.
Data cleaning using regular expressions.

Module 5: Data Visualization Tools (Tableau/Power BI)

Introduction to Tableau/Power BI.
Creating interactive dashboards.

Data filtering and highlighting.
Connecting data from various sources.
Module 6: Statistics and Data Interpretation
Basic statistics (mean, median, mode, standard deviation).
Hypothesis testing.
Correlation and regression analysis.
Case study: Decision-making using data.
Module 7: Domain-Specific Analysis
Business analysis.
Market trend analysis.
Customer behavior analysis.
Module 8: Projects and Career Preparation
Project: Analyzing real-world datasets and creating reports.
Improving CV and LinkedIn profile.
Mock interviews and freelancing guidelines.

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