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9Data Science and Analytics BootcampProgram StructurePowered by ThriveDX, this program aims to provide you with the knowledge base and practicalexperience you need to obtain a data science and analytics role. The curriculum integrates real-worldprojects and training exercises in data storytelling, data analysis, and data science to provide thepractical experiences, tools, and insights you need to succeed as a data professional.In the Data Science and Analytics Bootcamp, you will attend lectures, take part in individual andgroup exercises, and gain access to virtual labs and real-world projects that teach you how to use data togain business insight while using data analytics and data science best practices.The Data Science and Analytics Bootcamp was designed for working professionals. The program offersflexible evening and weekend course schedules and consists of a total of 400 in-class hours focusing onthe materials above as well as additional components to ensure your success.You can look forward to finishing this course with at least three completed data projects and learning avariety of topics, including Excel, statistics, data analytics, data wrangling, SQL, scripting languages,machine learning, and artificial intelligence to jumpstart your professional portfolio.30-Hour Introductory CourseOver 30 hours, you will grasp an understanding of the datadriven business world as you gain exposure to different careerpaths and a variety of analytic tools. This course provides anaccurate representation of the skills you will acquire and theprojects you can hope to complete should you choose to pursuethe full Data Science and Analytics program.Portfolio ProjectsYou will complete three experiential training projects thatyou can showcase on your personal portfolio when applyingto jobs in the field: A data-driven visualization project for which you can choosefrom three datasets: financial data from a small business,astronomical data from NASA, and Twitter data regardingairline sentiment A query project that takes in a dirty dataset and allows youto demonstrate data wrangling techniques and executequeries against the dataset to create meaningful conclusionsfor the business A machine learning project that allows you to create amodel from scratch and leverage existing AI APIs to solvebusiness challenges with artificial intelligenceCareer ServicesThriveDX works with every learner to ensure they havethe best chance possible when applying for a position indata science and analytics. Together, we work on yourresume, LinkedIn profile, and interview skills. We alsoprovide internship placement assistance and connect youwith professional networking opportunities.You are given multiple opportunities throughout theprogram to learn the critical skills you need to besuccessful during the hiring process. At least two events,such as demo days and hackathons, provide you with theopportunity to build additional portfolio projects youcan use to demonstrate the skills you have acquired.»

10Data Science and Analytics BootcampProgram Structure»Experiential LearningThis hands-on program provides knowledge of industry tools, methods, and coding languages, including: Data Storytelling and Visualization Statistics and Probability Critical Thinking and InclusiveEngineering Practices Python Responsible Use of Data and AI Presentation and CommunicationMachine Learning (Supervised and UnsupervisedLearning, Natural Language Processing, NeuralNetworks) Extract, Transform, Load (ETL) and DataWrangling Pipelines Applied AI (Speech, Vision, Text, Language,Knowledge APIs) SQL and Queries MLaaS (AWS) Tableau and Power BICommitmentto SuccessTo ensure a quality match between you and the program, and to maintain thecompetitive integrity of each individual, a revolutionary educational model is rooted inan admissions process that assesses practical aptitude in your field of interest, alongsideyour theoretical knowledge of the subject.The 30-hour Introductory Course focuses on foundational material, hands-on training,and critical thinking to provide you with a taste of the field and the experience you needto be sure data science and analytics is the right career path for you. At the end of theIntroductory Course, you will take an assessment exam and evaluate your progress withan Admissions Advisor to determine if the program is suitable for you.

11Data Science and Analytics BootcampProgram FlowThe Data Science and Analytics Bootcamp is divided into three parts. The first group of courses covers thefundamentals of how data can be used to tell a story and how the combination of statistics and probability give youthe tools to interpret the data and solve business problems. It reinforces that you are an advocate for the truth thedata represents, and you will learn to be an effective storyteller for that data. The second part focuses on the mostcommon tasks associated with data analytics, often called data wrangling. This includes cleaning data, structuringdata, and transforming data to prepare it for visualization or for use in a machine learning model. The third sectionfocuses on taking those foundational data skills and using them to solve the most common business problemsusing programming skills, machine learning, and applied artificial intelligence.Part 1: Data-Driven StorytellingIn these courses, you will learn the importance of being an advocate for the truth of data you are given to analyze.Part of that is understanding how to use data to tell the story about challenges impacting the business, as well asthe ability to offer solutions to those challenges.In the Data Science and Analytics Bootcamp, you will learn the principles of how data is collected, transformed,and used from day one. The fundamentals are taught with user experience in mind, and best practices areconsistently explained in each course.Part 2: Data Wrangling and AnalyticsIn these courses, you further apply the steps for a data project life cycle to include ethically sourcing data,combining data, wrangling data, and interacting with a database via programming SQL queries.Part 3: Data Science and Business IntelligenceIn the first two courses, you learn about business intelligence tools and big data. These tools are invaluable asyou progress through a deeper data project life cycle, where you have much more advanced and flexible methodsavailable to fulfill your needs. Additionally, you utilize scaffolding to build upon your prior knowledge to reinforcethe data sourcing, data wrangling, data analysis, and data visualization steps.In the last two courses, you delve into and constantly reinforce the importance of not only being able to usewhichever advanced tools your use case requires, but also the need to ensure that the complexity of the tool isbalanced with explainability. The more complex a tool is, the harder it is to explain it to stakeholders and decisionmakers. High accuracy and recall scores are great, but if you cannot explain what is going on in the backgroundand how the results were predicted, then you have lost half of your value to a decision-maker. Further, you arechallenged to ensure you are ethically building your feature selection and ensuring that the algorithm or model isinclusive and representative of everyone without marginalizing any group.»

12Data Science and Analytics BootcampWhat's 12 SpecializedCourses3 MilestoneProjects400 In-ClassHours3 DedicatedTest PreparationWorkshopsPrerequisites You are not required to have a background in any relatedfield, but should be prepared to learn technical concepts at arapid pace. Professional evaluation and admission exam

Data Science and Analytics BootcampIndustry CertificationsPreparation assistance for certification exams** includes the following:† Microsoft Certified: Data Analyst Associate IBM Data Analyst Professional Certificate IBM Data Science Professional Certificate AWS Cloud PractitionerWith these certifications, those completing the Data Science and Analytics Bootcamp can continue growing acareer as a data professional.††* While the curriculum covers much of the knowledge needed to perform well on industry exams, this program is not a test-preparation program, where the primaryfocus is your performance on the exam. The program is designed to teach in-demand knowledge for today's workforce.** Certification exams are not conducted as part of the program and require additional costs not included in tuition.† The test preparation workshops are not mandatory and are not part of the program curriculum. The workshops are designed to provide extra resources and help forthose who wish to take specific exams.†† You must have a minimum of one year of cumulative work experience in the specific cloud provider in order to be certified.The ThriveDX DifferenceThe University of Wisconsin–Madison’s Data Science and Analytics Bootcamp was developed inpartnership with ThriveDX (formerly known as HackerU). Originally founded in Israel, ThriveDX is oneof the world’s premier digital education providers with more than 15 years of global experience poweringcareer-change programs that help adult learners join the digital economy. This program leverages industryleaders to develop and teach curriculum tailored to today’s job market, including hands-on simulation labsthat support individuals aspiring to build a career in technology. ThriveDX partners with many top-tieruniversities to offer accelerated professional development programs for learners from all backgrounds.13

14Data Science and Analytics BootcampProgram BreakdownBy CourseCourse 1Introductory Course30HoursIn the first 30 hours, you are introduced to core data scienceand analytics topics, such as computing basics and the datalife cycle. You will have the opportunity to learn the basics of aJupyter notebook and interact with a Titanic dataset. You willpull the project materials from a GitHub repository and walkthrough it in a Google Colaboratory notebook. You can thenlook forward to completing three more projects throughout theremainder of the program to add to your personal portfolio.Before taking the Introductory Course, you should have:1.A reliable machine that is 10 years old or less2.A typing speed of 30 WPM or better3.Basic knowledge of using computers, such as howto open programs, point and click, and navigate to awebsite via a web browser4.Knowledge of basic math through algebraTopics: SQL Advanced Querying Debugging SQL Queries Basic Data Modeling Database ManagementCourse 3Statistics and Probability36HoursTopics:This course aims to enlighten you on how statisticsand probability are used in business decision-making.This course aids you in building a strong foundation indescriptive statistics, conditional probability, and advancedmodeling techniques. We use Microsoft Excel to providea practical application to theoretical discussions. Youdevelop the ability to approach real-world problems froman analytical perspective with confidence. Git and GitHubTopics: Scripting Descriptive Statistics Data Life Cycles Hypothesis Testing Computing Basics Probability Theory Intro to Data Projects Correlation Analysis of Variance (ANOVA) Regression Sampling TechniquesCourse 2SQL and Databases30HoursThis course provides you with an introduction to SQL,a popular language used to query databases. Using SQL,you will import data into databases, query data, join datatogether, filter and sort data, create views, and export data.Further, this course introduces you to database design andteaches you how to manage your own database.

Data Science and Analytics BootcampCourse 4Data Storytelling18HoursCourse 5Advanced SQL Programming30HoursIn this course, you discover the power of a story and howto develop a story arc around your data goals. Successfullycommunicating data insights depends on the audience ofstakeholders and the story points that speak to their needsand expectations. You continue to keep a data story threadthroughout the entire data wrangling adventure as youframe your data goals with purpose.Building upon the skills you gained in the SQL andDatabase course, this course extends your skill in SQLprogramming and covers topics such as stored procedures,functions, common table expressions (CTEs), and queryoptimization. You also develop ETL scripts and datapipelines combining the use of SQL and Python.Topics: Stored Procedures SQL Functions SQL Best Practices Debugging SQL Code Query Optimization ETL and Data Pipelines Public Speaking Story Arcs Requirements and Goals Story Narratives Personas, User Stories, and Scenarios Communicating Insights Engage the AudienceMilestone Project 1Building and PresentingData StoriesCourse 6Python Programming3HoursThis milestone project allows you to explore your skills inthe areas of statistics, Excel, SQL, and data storytelling.You have the opportunity to demonstrate your abilityto clean and manipulate a dataset. Additionally, youperform advanced statistical analysis on the data usingsummary statistics, linear regression, and modeling.Finally, you put your visualizations and insights into acoherent data story to present to your classmates. Theinstructional team formally reviews the data analyticsmilestone project. You then incorporate the project intoyour GitHub portfolio.Topics: Data Analysis ToolPak Visualizations Storyboarding Team Collaboration SQL Queries Presentation SkillsTopics:21HoursIn this course, you explore the fundamental conceptsof programming and learn how to structure theiranalyses. Topics include core programming conceptssuch as expressions, data types, variables, functions,loops, and arrays. Practice your coding skills throughbuilding highly structured and maintainable codeusing Jupyter notebooks.Topics: Variables, Loops, Arrays, Functions Data Types Dicts and Lists Jupyter Notebooks15

16Data Science and Analytics BootcampCourse 740Data WranglingHoursDevelop core data wrangling skills by expanding yourPython programming skills. Explore a series of data analysisprocesses from sourcing, curating, and importing data toexploratory data analysis, data cleansing techniques, anddata visualization techniques. Next, expand your toolboxby using industry-standard software to automate datawrangling processes.Data Collection andCuration Exploratory DataAnalysis Data Cleansing Visual AestheticsMilestone Project 2 Data Ingestion Presentation Data PreparationCourse 942Business IntelligenceHoursEthical Data Practices ETL/ELT ProcessesTopics:18HoursData Integration, Preparation,Reporting, and Presentation Dashboarding Data Visualization Benchmarking Sorting, Filtering, and Creating Metrics Joining TablesCourse 1060Machine LearningTopics:Effective DataVisualizationsData Reporting Explore visual dynamics and principles to produce effectivedata visualizations that show the most important parts ofdata to stakeholders in a clear and simplified way. Feature EngineeringTechniquesVisual CommunicationsVisual DynamicsPortfolios TechniquesCourse 8 Build upon visual communication concepts by learningto use popular industry business intelligence tools tocreate insightful analyses and visualizations. Developand apply best practices for reporting, graphs andcharts, and dashboards in a way that can be applied inany business intelligence application.Topics: Topics:3HoursThis milestone project focuses on developing yourability to attain, transform, investigate, and presentdata throughout a data project life cycle. Demonstrateyour ability to build data pipelines and wrangle datainto a usable format for downstream data visualizationand analytics. Present your reports and findings toclassmates and then incorporate the project into yourGitHub portfolio. The instructional team reviewsprojects in this milestone.HoursAnalyze a variety of use cases in a business context fordetermining appropriate machine learning methods toapply. Through a series of Python lectures and labs andusing Jupyter notebooks, investigate and apply supervisedand unsupervised machine learning algorithms, includingclassification, clustering, association rules, and time-seriesforecasting. Next, explore several advanced methods,including natural language processing, neural networks,and deep learning.Topics: Supervised andUnsupervisedLearningClassificationand ClusteringAlgorithmsRegression Association Rules Time-Series Analyses Natural LanguageProcessing Deep Learning

Data Science and Analytics BootcampCourse 1130Big DataHoursIn this course, examine core concepts and methods usedfor big data and IoT, including characteristics of big data,data warehousing, data lakes, data virtualization, andcloud-based data infrastructure services. Build upon yourprevious knowledge of Python by using PySpark to accessbig data and create analytics models.Topics: Data Warehousing, Data Lakes, and Hubs Data Virtualization Cloud Services Streaming Data IoT Database Scaling Spark and PySparkMilestone Project 3Capstone Project: DeliveringInsights and Presentations8HoursMeet the challenge of presenting your data insights andvisualizations clearly and with ease to diverse types ofstakeholders. Learn how to organize data visualizationsaround a goal and integrate a story arc to keep youraudience engaged. Work on your own individual projectthat incorporates the skills and knowledge you gainedthroughout the program. This milestone culminates ina final project presentation that capitalizes on your dataanalysis, data storytelling, and presentation skills. Finally,share your work by uploading your completed project toyour GitHub portfolio.Topics:Course 12 Public Speaking Skills Delivering Insights Organizing andPresenting DataStories Understanding YourAudience Decision-MakingProcesses Building Portfolios21Applied AIHoursCourse 13After the introduction to machine learning-created AI inthe previous course, explore a variety of pre-packaged AIcloud services offered by leading providers like Microsoft,Amazon, and Google. AI provides a more targeted dataanalytics experience, as it produces a greater amount ofdata insights through various applications of computervision, speech recognition, natural language processing,and robotics.Career ServicesTopics:Topics:10HoursYou will integrate with Career Services and the careercurriculum to acquire the knowledge and skills to besuccessful in the digital job market. This preparationensures you possess the tools to readily apply toopportunities in the field. AI Cloud Services Search Engine AI Resume Building Computer Vision andSpeech Deploying AI Job Search Using Python for AI Interview PreparationNatural LanguageProcessing17

Program SummaryIn-ClassHoursCoursesIntroductory Course30SQL and Databases30Statistics and Probability36Data Storytelling18Milestone Project 1: Building and Presenting Data Stories3Advanced SQL Programming30Python Programming21Data Wrangling40Visual Communications18Milestone Project 2: Data Integration, Preparation,Reporting

gain business insight while using data analytics and data science best practices. The Data Science and Analytics Bootcamp was designed for working professionals. The program offers flexible