Data Analytics

With Python and Power BI

Elevate your expertise with our immersive bootcamp training sessions, taking your tech skills to new heights.

Data Analytics

What is Data Analytics?

Data analytics is about examining data to find useful patterns and insights. It helps make informed decisions and solve problems by using statistical and computational methods. From understanding customer preferences to improving operations, data analytics is crucial for smart decision-making.

What is Python?

Python acts like a decoder ring for your data, helping you unlock hidden patterns and stories. Imagine sifting through mountains of information, then with a few lines of Python code, you uncover trends, connections, and insights you never knew existed. This empowers you to make data-driven decisions, solve mysteries in your data, and ultimately, gain a deeper understanding of the world around you.

Core Focus

  • Follow the design process

    Foundational Data Skills

    Learn key analytical skills and tools: data cleaning, analysis, visualization (spreadsheets, SQL, R, Tableau).

  • Apply UX concepts

    Data Organization

    Understand data cleaning, organization, and analysis techniques with spreadsheets, SQL, and R programming.

  • data present icon

    Present Data

    Develop proficiency in visualizing and presenting data findings through dashboards and popular visualization platforms.

  • Python

    Convert data to dashboards in a flash. Craft impactful data stories with Python's visualization tools, all through code.

Data Analytics Program

Our Fall 2024 Data Analytics program has closed applications.

In today's data-driven world, the demand for skilled data analysts continues to rise. To address this need and empower aspiring data professionals, we offer a comprehensive Data Analytics Training and Apprenticeship Program. This program is designed to equip participants with the fundamental skills, tools, and knowledge required to excel in the field of data analytics. By focusing on practical hands-on training and real-world case studies, this program aims to bridge the gap between theoretical knowledge and practical application, fostering the growth of the next generation of data analysts.

Program Dates:

  • Learn: October 21st, 2024 to February 28th, 2025

  • Earn:  March 2025 to May 2025

Time Commitment: Mondays through Thursdays, 9am-2pm, for 30-40 hours a week, including class time and personal work time on assignments.

Please note that this is a hybrid program and will require meeting in-person in Saint Paul once a week.

Cost: Free for eligible participants - this cohort is funded through the Learn and Earn Program

For eligibility criteria, please check the Learn and Earn Program page

Data Analytics Curriculum

Course 1: Foundations of Data Analytics

  • Understanding key data analytics concepts

  • Role of spreadsheets, query languages, and data visualization tools

  • Introduction to the role of a data analyst

Course 2: Problem-Solving and Data-Driven Decisions

  • Application of problem-solving roadmaps

  • Incorporating data into decision-making processes

  • Basic spreadsheet tasks for data organization

Course 3: Data Preparation Strategies

  • Factors influencing data collection decisions

  • Addressing bias in data

  • Introduction to databases and their components

  • Best practices for data organization

Course 4: Data Cleaning Techniques

  • Understanding data integrity and risks

  • Basic SQL functions for data cleaning

  • Crafting effective SQL queries

  • Verifying data cleaning results

Course 5: Data Analysis and Synthesis

  • Importance of data organization for analysis

  • Data conversion and formatting essentials

  • Utilizing SQL queries to combine data from multiple tables

  • Conducting basic calculations in spreadsheets

Course 6: Data Visualization Mastery

  • Leveraging data visualizations to communicate findings

  • Introduction to Tableau for data visualization

  • Exploring data-driven storytelling

  • Principles of effective data presentation

Course 7: Programming with R for Data Analysis

  • Introduction to the R programming language

  • Core concepts of R programming

  • Creating visualizations in R

  • Formatting content using R Markdown

Course 8: Python's Data Science Toolkit

  • Learn core Python concepts to handle your data.

  • Master wrangling techniques with libraries.

  • Craft impactful visualizations.

  • Present your findings clearly and effectively.

Course 9: Data Analytics Capstone Project

  • Distinguishing capstone, case study, and portfolio projects

  • Key attributes of a complete case study

  • Application of data analysis process to real-world data

  • Leveraging case studies/portfolios in job communication