Data Analyst Professional Master’s Program
Course Name - Data Analyst Professional Master’s Program
This course is designed to provide students with a comprehensive understanding of data analysis.
Course Overview
This course provides a comprehensive introduction to data analytics, equipping learners with the skills to collect, clean, analyze, and visualize data for actionable insights. Starting with foundational concepts, it covers essential tools like Excel, SQL, Python/R, and visualization platforms like Tableau and Power BI. Learners gain hands-on experience in statistical analysis, big data processing, and business intelligence reporting. The course culminates with a capstone project to apply skills to real-world scenarios and includes career development guidance to prepare learners for roles in data analytics.
Course Type
Entry-Level to Intermediate (suitable for beginners with progression to intermediate topics).
Course Objectives
– Introduce the principles and importance of data analytics in business.
– Equip learners with practical skills in data collection, cleaning, and manipulation.
– Teach statistical analysis and visualization techniques to uncover insights.
– Familiarize learners with tools like Excel, SQL, Python/R, and big data platforms.
– Develop competencies in business intelligence reporting and storytelling with data.
– Enable learners to showcase their skills through a real-world capstone project.
What You'll Learn
– Understand the data analytics lifecycle and its significance in decision-making.
– Master data cleaning techniques and analysis using tools like Excel, SQL, and Python/R.
– Apply statistical concepts such as hypothesis testing and regression analysis.
– Create compelling data visualizations and dashboards in Tableau and Power BI.
– Work with big data technologies like Hadoop and Spark for large-scale processing.
– Build effective business intelligence reports and present data-driven solutions.
– Gain confidence in pursuing a career in data analytics with resume and interview preparation.
Duration:
Approximately 120–150 hours, including hands-on exercises, projects, and career development modules.
Requirements:
– A computer with internet access.
– Installed tools such as Excel, Python/R (Jupyter Notebook or RStudio), and a database platform (MySQL, PostgreSQL, or similar).
Pre-requisite:
– Basic computer literacy.
– No prior programming or analytics experience required.
Target Audience
– Beginners aspiring to enter the field of data analytics.
– Business professionals looking to enhance decision-making with data-driven insights.
– Students or career changers seeking foundational skills in analytics.
– Entrepreneurs and managers aiming to understand data analytics for business growth.
Batch Details
Batch Start Date
Batch Timing
Batch End Date
Batch Days
Curriculum
- What is Data Analytics?
- Importance of Data Analytics in Business
- Roles and Responsibilities of a Data Analyst
- Data Types and Sources
- Data Collection Methods (surveys, web scraping, APIs)
- Data Cleaning Techniques (handling missing data, outliers, duplicates)
- Basics of Excel for Data Analysis
- Functions, Formulas, and Pivot Tables
- Introduction to Excel Macros
- SQL Fundamentals (SELECT, WHERE, JOIN, etc.)
- Querying Databases and Working with Tables
- Advanced SQL (Subqueries, Aggregate Functions)
- Introduction to Python/R
- Data Wrangling using Pandas (Python) / Dplyr (R)
- Statistical Analysis using Python/R libraries (NumPy, SciPy, etc.)
- Descriptive Statistics (mean, median, mode)
- Probability and Distributions
- Hypothesis Testing, Regression Analysis, Correlation
- Data Visualization Fundamentals
- Creating Visualizations in Excel, Tableau, Power BI
- Advanced Dashboards and Storytelling with Data
- Introduction to Big Data and Hadoop
- Using Spark for Data Processing
- Working with NoSQL Databases
- Business Intelligence Tools
- Building Effective Reports and Dashboards
- Case Study: Real-World Business Reporting
- Real-World Data Analysis Project
- Presenting Insights and Solutions
- Resume Building for Data Analysts
- Interview Preparation
- Networking and Job Search Strategies
This course is ideal for aspiring Data Analysts, business professionals, and anyone looking to enhance their data analytics skills.
FAQ
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