Data Analytics · Beginner
Data Analytics Bootcamp
A complete beginner-to-analyst curriculum covering Python, SQL, Pandas, data cleaning, exploratory analysis, visualization, and basic statistics.
- Price
- $79
- Level
- Beginner
- Duration
- 24 hours
- Lessons
- 68 lessons
- Projects
- 10 hands-on projects
- Prerequisites
- None — no programming experience required
Overview
The Data Analytics Bootcamp is a 24-hour, 68-lesson curriculum that takes you from no experience to completing full data analysis projects. It combines the core skills of a working analyst — Python, SQL, and Pandas — into one structured path with 10 hands-on projects.
The bootcamp starts with Python fundamentals and SQL querying, then moves into the daily workflow of an analyst: cleaning messy datasets, exploring them systematically, visualizing findings, and applying basic statistics to interpret results honestly.
Every stage ends with a project, and the final capstone walks you through a complete analysis: framing a question, gathering and cleaning data, exploring it, and presenting conclusions.
What you'll learn
- Write Python for data work: variables, loops, functions, and collections
- Query relational databases with SQL: SELECT, JOINs, and aggregation
- Manipulate datasets with Pandas DataFrames
- Clean real-world data: missing values, duplicates, and inconsistent formats
- Explore datasets systematically with summary statistics and grouping
- Visualize data with clear, honest charts
- Apply basic statistics: distributions, correlation, and averages done right
- Complete 10 projects, including a full end-to-end capstone analysis
Curriculum
8 modules · 68 lessons · 24 hours of material
Module 1 — Python Foundations
- Setting up your analysis environment
- Variables, types, and operations
- Conditions, loops, and functions
- Lists and dictionaries for data work
Module 2 — SQL Foundations
- SELECT, WHERE, and ORDER BY
- Aggregation with GROUP BY
- JOINs across tables
- Project: answering questions with SQL
Module 3 — Pandas Essentials
- DataFrames and Series
- Loading data from CSV and SQL
- Selecting, filtering, and sorting
- Project: first Pandas analysis
Module 4 — Data Cleaning
- Finding and handling missing values
- Fixing types, formats, and duplicates
- Combining messy sources
- Project: cleaning a real-world dataset
Module 5 — Exploratory Analysis
- Summary statistics that matter
- Grouping and comparing segments
- Finding patterns and outliers
- Project: exploratory analysis report
Module 6 — Data Visualization
- Choosing the right chart
- Building charts from DataFrames
- Avoiding misleading visualizations
- Project: visual analysis story
Module 7 — Basic Statistics
- Distributions and spread
- Correlation and its limits
- Comparing groups honestly
Module 8 — Capstone Project
- Framing an analytical question
- Gathering, cleaning, and exploring the data
- Drawing and presenting conclusions
Who this course is for
- Career changers targeting a data analyst role
- Beginners who prefer one structured path over piecing courses together
- Business professionals who want to analyze data themselves
- Students building a portfolio of analysis projects
Prerequisites
None — no programming experience required
Course outcomes
By the end of this course, you will be able to:
- Carry out a complete data analysis from raw data to conclusions
- Use Python, SQL, and Pandas together in one workflow
- Produce clear visualizations and statistically sound summaries
- Finish with 10 portfolio-ready projects, including a capstone
Frequently asked questions
Does the bootcamp overlap with the Python and SQL courses?
There is intentional overlap in the foundations: Modules 1 and 2 condense the essentials of Python and SQL. The bootcamp then goes further into cleaning, exploration, visualization, and statistics, which the standalone courses do not cover in depth.
How long does the bootcamp take?
It contains 24 hours of material across 68 lessons and 10 projects. At 4–5 hours per week, most learners complete it in 6–8 weeks.
Is this enough to apply for data analyst jobs?
The bootcamp covers the core technical skills asked of junior analysts and produces 10 portfolio projects. Pair it with the Data Analyst Learning Roadmap guide for the broader picture, including portfolio and practice advice.