What is The Data Analyst Course, and what topics does it cover? Why is it different from other online data analyst courses?
The Data Analyst Course is a training program that teaches the fundamental skills to become a job-ready data analyst. Unlike other online courses that neglect the crucial step of cleaning and preprocessing raw data, this course covers this aspect extensively.
The course covers the following topics:
Data collection-Data collection is the process of gathering and measuring information from various sources to create a dataset for analysis. It can involve various methods such as surveys, interviews, observations, and automated data collection. Collecting high-quality data is crucial for accurate analysis and decision-making and requires careful planning and consideration of the sources and methods used.
Data cleaning-Data cleaning is a data preprocessing step that involves identifying and correcting errors, inconsistencies, and inaccuracies in raw data. This process includes removing duplicate records, dealing with missing values, and standardizing data formats.
Data preprocessing-Data preprocessing is a critical step in data analysis that involves cleaning, transforming, and preparing raw data for analysis. This process includes identifying and handling missing or inconsistent data, dealing with outliers, and transforming data into a suitable format for analysis.
Data visualisation-Data visualization is a crucial aspect of data analysis and presentation, as it enables us to communicate complex information in a clear and accessible manner. Various charts and graphs, such as bar charts, line charts, histograms, and pie charts, are useful tools for representing different data types and highlighting important trends and patterns.
Excel Tools– Excel offers a wide range of miscellaneous data analysis tools, including Solver, which can be used to optimize solutions for complex problems. These tools can help users gain valuable insights into their data and make more informed decisions, improving their productivity and effectiveness in their work. With these tools, users can unlock the full potential of Excel for their data analysis needs.
SQL-Structured Query Language (SQL) is a programming language used to manage and manipulate relational databases. SQL is used to create, modify, and retrieve data from databases using a range of commands and functions. It is widely used in data analysis, business intelligence, and data management applications. SQL knowledge is valuable for anyone working with data, enabling them to extract meaningful insights from relational databases.
What Will You Learn?
- Practice with real-world data
- Complete a Data Cleaning exercise
- Learn Data Visualization
- Add data analytical tools to your skillset
- Start using MySQL
- Pivot Tables
- Data Processing
- Work with Data Sets
- Connect to different data sources such as Excel, Google Sheets
Lesson 1: Digital Literacy – week 101:33:09
Digital Literacy 2
Lesson 1: Digital Literacy 2 – week 202:31:05
Introduction to Data Analytics
Introduction to Data Analytics (1) – Week 403:28:48
Spreadsheets (1) – Week 504:47:09
Data Analysis Using Spreadsheet 1
Data Analysis Using Spreadsheet 1 (Excel functions and data cleaning processes) Week 703:16:29
Data Analysis Using Spreadsheet 2
Data Analysis Using Spreadsheet 2 – (Data Visualization) Week 802:02:08
Introduction to SQL02:02:08
SQL (2) – Week 902:58:42
Introduction to R
Introduction to R 1(RStudio) – Week 1003:04:01
R – Week 1100:00
Lesson 1: Continuation of R – Week 1200:00
Lesson 2: Continuation of R00:00
Lesson 1: Introduction to Tableau – Week 1302:58:11
Lesson 1: R – Week 1444:02
Lesson 2: Problem solving00:00