Learning Paths

This badge is earned by successfully completing all of the courses in the Python for Data Science path at Maven Analytics.

PATH HOURS: 76.0

PATH DESCRIPTION:

This path is for data professionals looking to build job-ready data science & ML skills with Python.

We'll start by mastering the foundations of data prep & EDA, including scoping projects, gathering & cleaning data, performing exploratory data analysis, and preparing the data for modeling.

Next we'll dive into Regression Analysis, a popular supervised learning technique for making predictions with numerical data. We'll introduce simple & multiple linear regression, review key model assumptions, and walk through the steps for testing and validating your models. We'll also cover multiple techniques for regularized regression and time series analysis, including ridge & lasso regression, moving averages, decomposition, and more.

From there we'll explore Classification Modeling, another supervised learning technique for making predictions with categorical data. We'll build k-nearest neighbors and logistic regression models, review evaluation metrics like accuracy, precision & recall, then explore methods for working with imbalanced data. We'll then dive into decision trees and ensemble models, including random forests & gradient boosting.

Last but not least we'll cover Unsupervised Learning, a popular approach for discovering hidden patterns & relationships in data. We'll use clustering algorithms for segmentation & anomaly detection, and then leverage dimensionality reduction algorithms for visualizing complex data, identifying clusters, and building recommendation engines.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Machine Learning Foundations path at Maven Analytics.

PATH HOURS: 15.0

PATH DESCRIPTION:

This path is for data analysts or BI professionals looking to develop a strong, foundational understanding of popular machine learning tools and techniques.

Unlike most data science or ML courses, this is NOT about learning how to code with Python or R. Instead, we'll use familiar, intuitive tools like Microsoft Excel to break down complex models and visualize exactly how they work.

We'll start by introducing the machine learning landscape and workflow, and exploring common univariate & multivariate data profiling techniques like frequency tables, histograms, heat maps, scatter plots and more.

Next we'll dive into the world of supervised learning, and review key concepts like dependent vs. independent variables, feature engineering, splitting and overfitting. In course #2, we'll introduce powerful classification models, including decision trees, logistic regression, and K-nearest neighbors.

From there we'll cover the building blocks of regression modeling and time-series forecasting, and explore powerful techniques for identifying seasonality, predicting nonlinear trends, and measuring the impact of key business decisions using intervention analysis.

Last but not least we'll introduce the world of unsupervised learning, and break down powerful unsupervised techniques including cluster analysis, association mining, outlier detection, and dimensionality reduction.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Python for Data Analytics path at Maven Analytics.

PATH HOURS: 73

PATH DESCRIPTION:

This path is for BI analysts or data scientists looking to build job-ready Python skills and master the most popular libraries for data analysis and visualization.

We'll start by mastering the core building blocks of Python for analytics, including data types, properties, and foundational tools like variables, numeric and string operators, conditional logic, loops and functions.

Next we'll dive into NumPy & Pandas, two of the most popular Python packages for data analysis. We'll introduce arrays and array properties, common operations like indexing, slicing, filtering and sorting, and powerful methods for exploring, analyzing, aggregating and transforming dataframes.

From there we'll explore data visualization methods using Matplotlib & Seaborn. We'll introduce data visualization frameworks and best practices, review tools and techniques for building and customizing basic charts, then explore advanced formatting options and custom visuals.

Last but not least we'll use Plotly & Dash to build and deploy interactive visuals, dashboards, and web applications.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Tableau Specialist path at Maven Analytics.

PATH HOURS: 65

PATH DESCRIPTION:

This path is designed to help you build expert-level data prep, analysis and visualization skills using Tableau Desktop and Tableau Prep.

Our Intro to Tableau Desktop course is designed to get you up and running with the Tableau Desktop platform. You'll learn how to connect and transform datasets, explore sorting, filtering and grouping tools, define custom calculations and parameters, and tie everything together with dynamic, interactive dashboards.

From there we'll introduce Tableau Prep, and explore tools for combining, shaping, and cleaning raw data for analysis. You'll learn how to connect and configure sources, group, split and clean data, create custom LOD and analytic calculations, and use tools to join, aggregate and transform tables.

Next we'll dive into advanced, expert-level visualization topics in Tableau Desktop, ranging from data relationships and advanced calculations to predictive analytics and dynamic design techniques.

Our Tableau Speed & Performance course is all about building fast, scalable, and user-friendly dashboards by optimizing source data, filters, calculations, and visual design.

Finally, our Tableau Certification Prep course will review the exact skills you need to ace the Tableau Desktop Specialist and Certified Associate exams, with project-based demos, exam tips, and full-length practice tests.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the MySQL Specialist path at Maven Analytics.

PATH HOURS: 50

PATH DESCRIPTION:

This path is for database administrators or data analysts looking to build expert-level MySQL skills, and practice applying them to real-world projects and case studies.

We'll start with an introduction to database administration, where you'll learn how to design, optimize and manage relational databases with MySQL Workbench. You'll learn how to create and edit tables and schemas, insert and delete records, manage users and permissions, and apply advanced tools like triggers and stored procedures.

From there we'll review core techniques for single and multi-table analysis, including SELECT and CASE statements, table unions and joins, and database normalization best practices. You'll apply your skills to a number of advanced case studies, including website traffic analysis, measurement and testing, channel mix, product performance, user analysis, and more.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Excel Specialist path at Maven Analytics.

PATH HOURS: 90

PATH DESCRIPTION:

This path is for Excel users looking to build a deep, expert-level skill set, including formulas, charts, PivotTables, Power Query, and more.

We'll start with a deep dive into some of Excel's core capabilities, including formulas, charts & graphs, and PivotTables. You'll learn how to explore and analyze raw data, build custom visuals and interactive reports, and quickly expose patterns and insights with user-friendly pivots.

From there we'll dive into more advanced tools like Power Query, Power Pivot & DAX, introduce advanced dashboard design principles, and explore tips and techniques to help you maximize your productivity.

Finally, we'll wrap up with an exam prep course to help you earn your official MO-201 Excel Expert certification from Microsoft.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Data Visualization Expert path at Maven Analytics.

PATH HOURS: 93

PATH DESCRIPTION:

This path is about bringing your data to LIFE, with project-based courses featuring some of the most popular data visualization platforms, including Excel, Power BI and Tableau.

We'll start with Thinking Like an Analyst, a crash course designed to help you build a strong foundation for a successful career in data.

Next we'll review key data visualization and design principles, explore 20+ common chart templates, and introduce powerful techniques for building dynamic, interactive reports and dashboards in Microsoft Excel.

From there we’ll shift gears into Power BI Desktop, where we’ll build an entire data model and dashboard from the ground up. You'll learn how to bring your data to life with tree maps, gauges, KPI cards, slicers, parameters, and AI-driven visuals like key influencers and decomposition trees.

Finally we'll dive into one of the world's most popular data visualization platforms: Tableau Desktop. Using a hands-on and project-based approach, we'll transform raw data into stunning, interactive reports and dashboards.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Power BI Specialist path at Maven Analytics.

PATH HOURS: 74

PATH DESCRIPTION:

This path is for users looking for a comprehensive, hands-on guide to self-service business intelligence with Power BI Desktop, Power BI Service & Advanced DAX.

You’ll learn how to connect and prep data from external sources, build relational data models and DAX calculations, and design custom, interactive reports and dashboards with Power BI Desktop.

From there you’ll publish your work to the cloud with Power BI Service, create new apps and workspaces, and explore advanced tools like gateways, dataflows, row-level security, data-driven alerts, and more.

Finally, you'll build expert-level BI skills and solve real-world projects with advanced Data Analysis Expressions (DAX).

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.

This badge is earned by successfully completing all of the courses in the Business Intelligence Analyst path at Maven Analytics.

PATH HOURS: 105

PATH DESCRIPTION:

This path is for aspiring data looking to master a powerful stack of self-service business intelligence tools, including Excel, MySQL, Power BI and Tableau.

We'll start with Thinking Like an Analyst, a crash course designed to help you build a strong foundation for a successful career in data.

From there we'll dive into some of Excel's most powerful analytics tools (including formulas, PivotTables, data visualization and dashboard design), then shift into MySQL, one of the most versatile and practical languages for building, exploring and analyzing databases.

Next we'll dive into two of the most popular business intelligence platforms on the market. You'll master Power BI Desktop by designing and building full-scale data models and reports from scratch, then use Tableau to transform raw data into stunning, interactive dashboards.

Finally, we'll wrap with Launching Your Data Career, a step-by-step guide to finding your path, building your brand, acing the interview, and landing your data dream job.

This path is designed to help you learn job-ready skills, solve real business problems, and build a project portfolio to showcase your skills to peers and employers.