Data Analytics 101: Building Your Skillset from Scratch
Kickstart your career in data analytics with this hands‑on introduction to essential concepts, tools, and techniques—no prior experience required.
Kickstart your career in data analytics with this hands‑on introduction to essential concepts, tools, and techniques—no prior experience required.
In Data Analytics 101: Building Your Skillset from Scratch, you’ll embark on a structured journey from foundational theory to real‑world application. Over four modules, you’ll:
Understand the Data Ecosystem
– Learn key terminology (data types, sources, and lifecycle)
– Explore the role of a data analyst in modern organizations
Master Essential Tools
– Get comfortable with spreadsheets (Excel/Google Sheets) for cleaning and exploring data
– Dive into Python basics for data wrangling with pandas and NumPy
– Visualize insights using charting libraries and dashboard platforms
Develop Analytical Techniques
– Perform descriptive statistics and identify trends
– Build simple predictive models with regression analysis
– Apply best practices for data validation and quality assurance
Apply Your Skills
– Work through real datasets drawn from finance, marketing, and operations
– Collaborate on a capstone project to tell a data‑driven story
– Present findings through compelling visuals and executive summaries
By the end of this course, you’ll confidently navigate the entire analytics workflow—from asking the right questions and gathering data to producing actionable insights. Whether you’re switching careers, enhancing your current role, or simply curious about data, this beginner‑friendly program gives you the practical skills and portfolio project you need to stand out.
- SQL and its use cases
- Brief History of SQL
- Different Databases
- Popular DBMS’s
- SQL Terminology
- Setting up your Environment
- Creating a Sample Database
- Writing Basic SQL Queries
- SQL Basic Rules and Syntax
- Filtering and Organizing Data with Clauses
- Using Operators and Functions
- Summary
A computer with internet access
Basic proficiency in English
No prior experience in data analytics required
Willingness to learn and engage with course materials
Installation of required software (guidance provided during the course)
Understand the fundamentals of data analytics and its applications
Perform data cleaning and preprocessing techniques
Create insightful data visualizations using tools like Tableau
Apply statistical methods for data analysis
Develop predictive models using Python
Interpret and communicate data findings effectively
IT, Cybersecurity, DevOps, Cloud computing, Artificial Intelligence, AI
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Last Updated
Jun 03, 2025
Students
1
language
English
Duration
00h 00mLevel
beginner
Expiry period
Lifetime
Certificate
Yes
English
Certificate Course
1 Students
00h 00m