Data Analysis
About this learning track
Data Analysis involves examining, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. This field focuses on applying statistical and computational techniques to large datasets to identify patterns, trends, and relationships.
Data Analysts use tools such as Python, R, SQL, and Excel, along with visualization tools like Tableau and Power BI, to analyze data effectively. They work closely with stakeholders across various departments to provide insights that drive business strategies and improve performance.
What you will learn
- Data Cleaning and Preprocessing: Learn techniques to clean and prepare data for analysis.
- Statistical Analysis: Understand the principles of statistical analysis to interpret data accurately.
- Data Visualization: Master tools like Tableau and Power BI to create compelling data visualizations.
- Programming for Data Analysis: Gain proficiency in Python for data manipulation and analysis.
- SQL for Data Management: Learn to query and manage databases using SQL.
Requirements
- A working laptop
- Steady internet access
- A working mobile phone
- A learning attitude
Curriculum
Master statistical techniques, data visualisation and advanced analytics for real-world impact.
Week 1 - Introduction to Programming
Week 2 - Introduction to Data
Week 3 - Introduction to Data Analysis
Week 4 - Introduction to Python Programming
Week 5 - Data Structures and Libraries
This lesson provides an overview of the fundamental concepts of programming, including algorithms, control structures, data types, and syntax.
It aims to build a strong foundation in logical thinking and problem-solving skills, essential for writing efficient code.
At Learnable, you're given the chance to turn data into discovery, and insights into impact!
Obinna Okamgba
Path Lead
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