Fundamentals of Data Analysis (Basic and Advance) | FDABA
Created By: Training Head
What you'll learn
- Introduction to Data Analysis
- Excel Basics
- Data Visualization Principles
- Tableau Usage
- Data Cleaning Techniques
- SQL Fundamentals
- Descriptive Statistics
- Inferential Statistics
- A/B Testing
- Advanced Techniques
Requirements
Participants need a computer with internet access. No prior experience in data analysis is required. Basic computer literacy is recommended. The course is designed for beginners seeking foundational knowledge in data analysis. Enthusiasm for learning and a willingness to engage in hands-on exercises and projects are essential. Access to Microsoft Excel and Tableau software is preferred but not mandatory, as alternative tools may be provided for practice.
Course Description
The Foundations of Data Analysis course provides a comprehensive introduction to essential principles and techniques for interpreting data effectively. Designed for beginners, the course covers basic data manipulation with Excel, data visualization using Tableau, and data cleaning with SQL. Participants will delve into statistical analysis, including hypothesis testing and A/B testing, and explore advanced techniques like regression analysis, time series analysis, and machine learning. Through a capstone project, participants will apply learned concepts to real-world datasets, crafting comprehensive data analysis reports. Recommended resources and industry case studies supplement learning. Upon completion, participants are prepared for roles such as Business Analyst, Data Scientist, Financial Analyst, and more. No prior experience required, making it ideal for those seeking a foundational understanding of data analysis.
Course Content
Module 1: Introduction to Data Analysis (2 weeks)
1 lectures, 01:00:00 hrs
Module FDABA 1
Module 2: Data Visualization (3 weeks)
1 lectures, 01:00:00 hrs
Module FDABA 2
Module 3: Data Cleaning and Wrangling (2 weeks)
1 lectures, 01:00:00 hrs
Module FDABA 3
Module 4: Statistical Analysis (4 weeks)
1 lectures, 01:00:00 hrs
Module FDABA 4
Module 5: Advanced Data Analysis Techniques (3 weeks)
1 lectures, 01:00:00 hrs
Module FDABA 5
Module 6: Capstone Data Analysis Project (4 weeks)
1 lectures, 01:00:00 hrs
Module FDABA 6
Live Projects
1 lectures, 01:00:00 hrs
Module FDABA 7
Very interactive and beginner-focused. The live projects made me feel like I was working in a real business environment. Definitely boosted my confidence to take up data roles.
The content was delivered in a very practical and easy-to-understand way. Excel and Tableau tutorials were excellent. After finishing the capstone, I actually used my project in a job interview!
Clear, structured, and hands-on — just what a beginner needs. Loved the mix of tools and techniques. Would have liked a bit more practice on statistical formulas, but still a great learning experience.
This course is perfect for anyone starting their data journey. I appreciated the focus on real-world application rather than just theory. The regression and time series parts were eye-openers.
I liked how accessible everything was. The SQL portion was a bit challenging for me, but the explanations were clear enough to follow. A great course to start a career in analytics.
I was new to data but this course gave me a full overview — from basic Excel formulas to inferential statistics. The live projects really made a difference in learning by doing.
The Tableau module was very insightful and fun to work with. I loved how they used real datasets for practice. A few areas could use deeper explanation, but overall very helpful.
Great beginner-friendly course! It covers everything from visualization to statistical analysis in a very practical way. I now feel more confident applying for analyst roles.
A solid course for beginners. I didn't have any prior experience in data, but the way topics were broken down made it easier to follow. I especially liked the A/B testing section — it was new and interesting.
This course gave me exactly what I needed to understand data analysis from scratch. The combination of Excel, Tableau, and SQL was perfect. The Capstone Project helped me apply everything practically.
