Applied Analytics Courses and Certifications

Applied Statistics for Data Analytics

63 ratings at Coursera

Learn descriptive statistics, probability distributions, confidence intervals, and hypothesis testing in spreadsheets, using large language models to formulate hypotheses, run calculations, and interpret results.

• Coursera
• 4 weeks, 9 hours a week
• Self-Paced
• Paid Course

Edureka Career Certificate

Applied Data Analytics

61 ratings at Coursera

Analyze data with Python, SQL, and Power BI: query and manipulate datasets, visualize with Matplotlib, Seaborn, and Plotly, and build predictive models and dashboards.

• Coursera
• 20 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 4 courses

Applied SQL For Data Analytics / Data Science With BigQuery

1268 ratings at Udemy

Go from SQL Zero to Hero and develop rich mental models for writing sophisticated SQL statements & solving problems.

• Udemy
• 13 hours 2 minutes
• Self-Paced
• Paid Course

Introduction to Clinical Data

517 ratings at Coursera

Construct analysis-ready datasets from patient timelines, mine clinical data from healthcare systems, handle unstructured text, images and signals, do electronic phenotyping, and confront fairness and bias.

• Coursera
• 8 weeks, 1 hour a week
• Self-Paced
• Paid Course

Career Certificate

Data Analytic Tools for Financial Management Course

4 ratings at Graduate School USA

Use Excel and InfoZoom to uncover anomalies, duplicates, improper payments, and aging receivables in federal financial data.

• Graduate School USA
• Self-Paced
• $579.00

Python for Finance

3 ratings at CreativeLive

Use Python’s financial libraries and APIs to gather, manipulate, and analyze company, economic, and SEC financial-statement data.

• CreativeLive
• 24 hours
• Self-Paced
• Paid Course

Edureka

Applied Data Analytics with Python and SQL

Learn to analyze data with Python: clean and manipulate datasets using NumPy and Pandas, query MS SQL Server, scrape web data, and visualize insights with charts.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Edureka

Applied Analytics Engineering and Visualization with dbt

Refactor dbt models with reusable macros and tests, tune materializations and joins, monitor pipeline freshness, and build KPI dashboards in a BI tool.

• Coursera
• 3 weeks, 3 hours a week
• Self-Paced
• Paid Course

Career Certificate

Applied Data Analytics

Automate tabular analysis with Python and Pandas, design Power BI dashboards, build data narratives with a context-conflict-resolution arc, and apply graph analytics to financial and logistics networks.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 4 courses

Career Certificate

Applied AI in Data Analytics

Use AI to work with data: build foundational AI knowledge, write effective prompts, and apply AI tools to analytics workflows to surface and communicate insights.

• Coursera
• 8 weeks, 5 hours a week
• Self-Paced
• Paid Course
• 3 courses

Career Certificate

Applied Data Science and Analytics

Run and interpret regression models in Excel, SPSS, and R, evaluate Big Data platforms like Hadoop, Spark, and BigQuery, and turn findings into KPI-driven strategic recommendations.

• Coursera
• 4 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 3 courses

Machine Learning for Healthcare

6 ratings

This course introduces students to machine learning in healthcare, including the nature of clinical data, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows.

• MIT OpenCourseWare
• 31 hours
• Self-Paced
• Free Video

AI in Healthcare Capstone

329 ratings at Coursera

Follow one patient's respiratory-symptom journey through a de-identified EHR and imaging dataset: build, evaluate, and deploy risk-stratification models while weighing regulatory and ethical issues.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Career Certificate

Sports Performance Analytics

287 ratings at Coursera

Build predictive models from MLB, NBA, NHL, Premier League, and IPL data, replicate Moneyball with statistical models, apply the Linear Probability Model, wearables data, and machine learning.

• Coursera
• 16 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 5 courses

Foundations of Sports Analytics: Data, Representation, and Models in Sports

209 ratings at Coursera

Analyze team and player performance in Python: compute Pythagorean expectation, build heatmaps and plots, fit regression models, and test the hot hand with NBA shot logs.

• Coursera
• 6 weeks, 8 hours a week
• Self-Paced
• Paid Course