Springboard & Amazon Career Choice: Data Analytics Career Program

Refresh your basic mathematical skills to start the course before moving on to visualizing data using multiple chart formats and finish with an introduction to the logical thinking frameworks analysts use to approach problems.

• Percentages and ratios
• Algebra as a data professional
• Basic to intermediate visualizations using charts

All data analysis starts with a question. But how does one ask the right question? Learn to think in a structured manner and break down problems into bite-sized chunks which can be tested. This will guide your analysis and prevent you from analyzing data for the sake of analysis.

• Structured thinking and problem statements
• Problem solving frameworks and processes
• Issue trees, hypotheses trees, and value driver trees

As a data analyst, your analyses will require a central theme and tangible business insights you can communicate to executives. In this unit, you’ll be introduced to common economic and financial concepts and use Microsoft Excel to build your first financial model. You’ll also be introduced to key statistical concepts used to measure performance.

• Financial concepts including revenue, operating expenses, EBIT Analysis
• Economic concepts including supply and demand curves, calculation of product elasticities
• Create a default financial analysis model using Excel
• Statistical concepts include descriptive statistics and inferential statistics

Navigating extensive sets of data to answer the burning questions of executives will be crucial to your career success. In this unit, you’ll learn what databases are, which ones to use in your analyses, and how to communicate with them to get the information you need efficiently.

• Introduction to advanced SQL and best practices in writing queries
• Report on business analyses using SQL reporting capabilities
• Introduction to Relational Databases

The ability to conduct data analysis in Python will set you apart in the job market. In this unit, you’ll learn the basics of Python and key Python libraries, including pandas, numpy, matplotlib, seaborn, and more. You’ll then use real data to perform your own importing, wrangling and extraction of insights that could be presented to an executive.

• Basic Python syntax
• Introduction to Jupyter and Jupyter Notebooks
• Introduction to Tabulated Data Analysis with Pandas
• Visualizing data and trends with Seaborn and Matplotlib
• Applications of Statistical Analysis and Outlier Detection with Python
• Practical exercises in Python with real data

Data analysts need to be adept at presenting the results of their analysis to the appropriate stakeholders. This is a high-demand skill that separates effective business-oriented data analysts from the rest. This unit covers best practices for presenting to both technical and non-technical audiences.

• Visualization tools such as Tableau and PowerBi
• Creating custom presentations via PowerPoint / Tableau
• Effective communication strategies, formats, and templates
• Presentation philosophies for different stakeholder groups
• Presentation practice across different forms

These units are designed to help you create a tailored job search strategy based on your background and goals. Learn how to craft a resume that stands out from the pack, evaluate companies and roles, practice interviews, and negotiate the best possible salary with your career coach supporting you at every step.

• Job search strategies for the software engineering industry
• Building a network and leveraging it to land interviews
• Creating a high-quality resume, LinkedIn profile, and cover letter
• Preparing for technical and non-technical interviews