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DesignU

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Data Analytics

Categories: DigiCorpers Program
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About Course

Designu_Data_Analytics

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.

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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
  • Excel
  • Data Processing
  • Work with Data Sets
  • Connect to different data sources such as Excel, Google Sheets

Course Content

Digital Literacy

  • Lesson 1: Digital Literacy – week 1
    01:33:10

Digital Literacy 2

Introduction to Data Analytics
The course will provide students with a foundational understanding of the principles and tools used in data analytics. Students will also learn to be familiar with core concepts, processes and tools needed to gain entry into data analytics.

Spreadsheets

Data Analysis Using Spreadsheet 1

Data Analysis Using Spreadsheet 2

SQL

Introduction to R

R

R

Tableau

Revision

Student Ratings & Reviews

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SO
7 months ago
This is such a goodwill and so thoughtful of DesignU that one learn data analystics for free. Big thumbs up