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This is your path to a career in Data Analytics. Learn in-demand skills to have you job-ready to succeed in an entry-level Data Analytics job
Pave your career path to become job-ready and put your skills to work
Have working knowledge of essential platforms (spreadsheets, SQL, Tableau, R programming) and when to use them in the data lifecycle
Understand how to translate a business question into a data analysis exercise, including transforming, visualizing, and modeling data
Know how to distill findings into actionable takeaways
Complete a capstone project to put it in your resume and portfolio to showcase your skills to hiring partners
You will gain a deeper understanding of foundational data analytics terminology and the role responsibilities of a data analyst. An introduction to the kind of jobs you might pursue after completing this program is also covered.
- Insight into practices & processes used by junior or associate data analyst in their day-to-day job
- Develop key analytical skills such as data cleaning, data analysis, & data visualization
- Discover a wide variety of terms and concepts relevant to the role of a junior data analyst
- Evaluate the role of analytics in the data ecosystem
- Conduct an analytical thinking self-assessment
- Learn about best practices in job search
- Explore job opportunities available upon program completion
Spreadsheet Basics | Database & Query Basics | Data Visualization (DataViz) Basics
Introduction to Data Analytics | Thinking Analytically | Exploring the world of Data | Setting up Data Toolbox | Discovering Data Career Possibilities
You will build on the topics introduced in the first course and cover how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs.
- Learn about effective questioning techniques that can help guide analysis
- Gain an understanding of data-driven, decision-making, & how data analysts present findings
- Explore a variety of real-world business scenarios to support an understanding of questioning & decision-making
- Discover how & why spreadsheets are an important tool for data analysts
- Examine the key ideas associated with structured thinking and how they can help analysts better understand problems and develop solutions
- Manage the expectations of stakeholders while establishing clear communication with a data analytics team to achieve business objectives
Spreadsheet Formulas & Functions | Asking SMART & Effective Questions | Dashboard Basics, including Tableau | Managing Team & Stakeholder expectations
Asking Effective Questions | Making Data-Driven Decisions | Learning Spreadsheet Basics | Managing Stakeholder Expectations
You will build on the topics introduced in the first two courses and cover how to use tools like spreadsheets and SQL to extract and make use of the right data for key objectives in an organized and protected manner.
- Find out how analysts decide which data to collect for analysis
- Discover how to identify different types of bias in data to help ensure data credibility
- Explore how analysts use spreadsheets & SQL with databases & data sets
- Examine open data & the relationship between & importance of data ethics and data privacy
- Learn how to access databases and extract, filter, & sort the data they contain
- Learn the best practices for organizing data & keeping it secure
Understanding Data Types, Fields, & Values | Writing Simple Queries | Metadata in Data Analytics | SQL Functions
Data Types & Data Structures | Understanding Bias, Credibility, Privacy, Ethics, and access | Databases: where Data lives | Organizing & Protecting your Data | Engaging in the Data Community (Optional)
You will build on topics introduced in previous courses and also explore how to check and clean data using spreadsheets and SQL. We also explore how to verify and report data cleaning results.
- Learn how to check for data integrity
- Discover data cleaning techniques using spreadsheets
- Develop basic SQL queries for use on databases
- Apply basic SQL functions for cleaning and transforming data
- Learn how to verify the results of cleaning data
- Explore the elements and importance of data cleaning reports
Statistics, Hypothesis Testing, & Margin of Error | Tools & Processes for Data Cleansing | Data Integrity
Before you clean, Check for integrity | All about Clean Data | Cleaning Data in SQL | Verify & report your cleaning results | Adding Data to your Resume (Optional)
You will explore the “analyze” phase of the data analysis process by learning how to organize and format the data using spreadsheets & SQL to help you look at and think about your data in different ways. Discover how to perform complex calculations on data to complete business objectives. Additionally, learners are exposed to how to use formulas, functions, & SQL queries to conduct analysis.
- Learn how to organize data for analysis
- Discover the processes for formatting and adjusting data
- Learn how to aggregate data in spreadsheets and by using SQL
- Use formulas and functions in spreadsheets for data calculations
- Learn how to complete calculations using SQL queries
Sorting & Filtering Data with SQL | Spreadsheet Calculations | SQL Calculations | Data Validation | Temporary & Pivot tables
Organising Data to begin Analysis | Formatting & Adjusting Data | Aggregating Data for Analysis | Performing Data Calculations
You will explore how to visualize & present data findings during the data analysis process. This module demonstrates how data visualizations, such as visual dashboards, can help bring data to life. You will also explore Tableau, a data visualization platform that helps create effective visualizations for presentations.
- Examine the importance of data visualization
- Learn how to form a compelling narrative through data stories
- Learn how to use Tableau to create dashboards & dashboard filters
- Learn how to use Tableau to create effective visualizations
- Learn the principles & practices involved with effective presentations
- Learn how to consider potential limitations associated with the data in your presentations
- Learn how to apply best practices to a Q&A with your audience
Design Thinking | Tableau Software | Data-Driven Storytelling | Dashboards & Dashboard Filters
Visualizing Data | Creating Data Visualizations with Tableau | Crafting Data Stories | Developing Presentations & Slideshows
You will explore he programming language known as R with an environment called RStudio. This course also covers the software applications and tools that are unique to R, such as R packages. You will also discover how to clean, organize, analyze, visualize, and report data in new and more powerful ways using R.
- Examine the benefits of using the R programming language
- Discover how to use RStudio to apply R to data analysis
- Learn the fundamental concepts associated with programming in R
- Explore the contents & components of R packages including the Tidyverse package
- Gain an understanding of dataframes and their use in R
- Discover the options for generating visualizations in R
- Learn about R Markdown for documenting R programming
R Programming Functions | R Programming Variables | R Programming Data Types, Pipes, & Vectors | Coding, Writing Functions, Accessing & Cleaning Data, & Generating Visualizations in R
Programming & Data Analytics | Programming using R Studio | More about Visualizations, Aesthetics, & Annotations | Documentation & Reports
You will have the opportunity to complete an optional case study. The case studies are commonly used by employers to assess analytical skills. For their case study, they’ll choose an analytics-based scenario, ask questions, prepare, process, analyze, visualize and act on the data from the scenario.
- Learn the benefits & uses of case studies and portfolios in the job search
- Discover real world job interview scenarios & common interview questions
- Discover how case studies can be a part of the job interview process
- Examine & consider different case study scenarios
- Have the chance to complete your own case study for your portfolio
Building a Job Portfolio | Practical, real-world Problem Solving | Clear Presentation of Data Findings | Showcasing Data Analytics Skills, Knowledge, & Technical Expertise
Learn about Capstone Basics | Putting your Certificate to Work | Aggregating Data for Analysis | Building your Portfolio (Optional) | Using your Portfolio (Optional)
Associate Analyst at Infosys
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