Udemy
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Data Analyst Bootcamp: Excel, SQL, Python, Power BI, Tableau
New
21 students

Data Analyst Bootcamp: Excel, SQL, Python, Power BI, Tableau

Master statistics, data tools, and real-world analytical thinking to launch or level up your data analyst career.
Last updated 8/2026
English

What you'll learn

  • Build a strong analytical foundation — statistics, probability, hypothesis testing, and data-driven reasoning used in real analyst work.
  • Master the essential toolkit — Excel, SQL, Python (pandas), Power BI, Tableau, and QuickSight for data cleaning, analysis, and visualization.
  • Communicate data with integrity — apply data quality checks, ethical best practices, and storytelling techniques that make insights clear and trustworthy.
  • Think and act like a working analyst — handle real business scenarios, stakeholder conflicts, and ambiguous problems with confidence and sound judgment.

Included in This Course

244 questions
  • Statistics, Probability & Analytical Thinking30 questions
  • Core Data Analysis Concepts & Applied Techniques40 questions
  • Data Quality, Ethics & Data Storytelling20 questions
  • Real-World Scenarios & Business Problem-Solving20 questions
  • Technical Tools: Excel, SQL, Python, Power BI, Tableau & QuickSight134 questions

Description

Data is the language of modern business — and this course is built to make you fluent in it. Whether you're starting from zero or brushing up before a career change, this Data Analyst course takes you from the fundamentals of statistics and probability all the way to hands-on mastery of the tools employers actually use: Excel, SQL, Python, Power BI, Tableau, and Amazon QuickSight.

You'll begin by building a rock-solid analytical foundation — understanding measures of central tendency, distributions, hypothesis testing, correlation, and probability — the mathematical thinking that separates a true analyst from someone who just makes charts. From there, you'll move into core data analysis concepts like predictive vs. descriptive analytics, regression, clustering, dimensionality reduction, and database fundamentals, connecting theory directly to real analytical workflows.

But technical skill alone isn't enough. This course places equal weight on data quality, ethics, and storytelling — teaching you how to spot bias, protect sensitive data, avoid misleading visualizations, and present insights that actually influence decisions. You'll also work through realistic, on-the-job scenarios: handling conflicting numbers from stakeholders, defending a small sample size, explaining a confusing metric to a non-technical manager, and knowing what to do when a CEO wants a chart in five minutes with messy data. These scenario-based lessons are designed to build the judgment and communication skills that separate junior analysts from trusted ones.

Finally, you'll get deep, practical training across the essential toolkit of a modern data analyst — from pivot tables and XLOOKUP in Excel, to joins and indexing in SQL, to pandas and DataFrames in Python, to building interactive dashboards in Power BI, Tableau, and QuickSight.

By the end of this course, you won't just know definitions — you'll think like an analyst, work like an analyst, and be ready to prove it. Whether your goal is landing your first data analyst role, transitioning from another career, or leveling up your current skill set, this course gives you the complete package: the math, the tools, the ethics, and the real-world judgment to succeed.

Who this course is for:

  • Anyone looking to break into the data analytics field, switch careers, or strengthen their existing analyst skill set — no prior data experience required.