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Certified Associate Data Analyst with Python (PCAD™)

Updated September 2026

61Skills
340Videos
49hTotal

Course Curriculum

One skill is free to watch — no signup needed. The other 60 premium skills unlock for your whole team with a CBT Nuggets plan.

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Machine Learning Algorithms: Classification Trees

Shaun WassellDuration: 50m11 videos

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  • Premium skill.Basics of Jupyter Notebooks50m · 10 videos
  • Premium skill.Introduction to NumPy47m · 11 videos
  • Premium skill.Working with Multidimensional NumPy Arrays51m · 9 videos
  • Premium skill.NumPy Array Operations48m · 11 videos
  • Premium skill.Introduction to Fancy Indexing in NumPy55m · 9 videos
  • Premium skill.NumPy Array Broadcasting In-Depth53m · 9 videos
  • Premium skill.Basic Data Analysis with NumPy Arrays49m · 11 videos
  • Premium skill.NumPy's Data Types In-Depth46m · 9 videos
  • Premium skill.Basics of Pandas Series47m · 11 videos
  • Premium skill.Basics of Pandas DataFrames46m · 9 videos
  • Premium skill.Generating Random Numbers with NumPy and Pandas51m · 11 videos
  • Premium skill.Working with Datasets in Pandas46m · 10 videos
  • Premium skill.Dataset Cleaning in Pandas50m · 11 videos
  • Premium skill.An In-Depth Look At Missing Values48m · 9 videos
  • Premium skill.The Basics of Pandas Dataset Grouping51m · 9 videos
  • Premium skill.Intermediate Dataset Grouping45m · 9 videos
  • Premium skill.Filtering Data in Pandas48m · 11 videos
  • Premium skill.Transforming Data in Pandas50m · 11 videos
  • Premium skill.Applying Functions in Pandas47m · 11 videos
  • Premium skill.Sorting Pandas Data Structures47m · 13 videos
  • Premium skill.Introduction to Web Scraping with BeautifulSoup50m · 11 videos
  • Premium skill.BeautifulSoup Types In-Depth47m · 9 videos
  • Premium skill.Finding Elements with BeautifulSoup53m · 11 videos
  • Premium skill.CSS Selectors For Web Scraping46m · 11 videos
  • Premium skill.CSS Combinators for Web-Scraping44m · 9 videos
  • Premium skill.CSS Pseudo-Classes for Web-Scraping45m · 9 videos
  • Premium skill.Introduction to XPath for Web-Scraping50m · 11 videos
  • Premium skill.Intermediate XPath Concepts48m · 11 videos
  • Premium skill.XPath Predicates Basics47m · 9 videos
  • Premium skill.Advanced XPath Predicates44m · 9 videos
  • Premium skill.Basics of Data Visualization with Matplotlib45m · 9 videos
  • Premium skill.Working with Scatterplots in Matplotlib45m · 11 videos
  • Premium skill.Working with Bar Charts in Matplotlib45m · 11 videos
  • Premium skill.Working with Pie Charts in Matplotlib44m · 9 videos
  • Premium skill.Statistical Visualization Basics with Matplotlib45m · 9 videos
  • Premium skill.Matplotlib Figures In-Depth49m · 11 videos
  • Premium skill.Adding Interactivity with Matplotlib Widgets49m · 9 videos
  • Premium skill.More Matplotlib Widgets47m · 9 videos
  • Premium skill.Introduction to Seaborn45m · 10 videos
  • Premium skill.Working with Seaborn's Relational Plots45m · 9 videos
  • Premium skill.Working with Seaborn's Categorical Plots46m · 11 videos
  • Premium skill.Machine Learning Algorithms: K-Nearest Neighbor45m · 11 videos
  • Premium skill.Machine Learning Algorithms: Linear Models48m · 11 videos
  • Premium skill.Machine Learning Algorithms: K-Means Clustering46m · 11 videos
  • Premium skill.Machine Learning Algorithms: Neural Networks46m · 9 videos
  • Machine Learning Algorithms: Classification TreesFree50m · 11 videos
  • Premium skill.Basics of Descriptive Statistics50m · 11 videos
  • Premium skill.Descriptive Statistics In-Depth49m · 11 videos
  • Premium skill.Correlation In Statistics48m · 10 videos
  • Premium skill.Inferential Statistics Fundamentals48m · 9 videos
  • Premium skill.Bootstrapping and Other Inferential Strategies52m · 11 videos
  • Premium skill.Introduction to SQL For Data Analysts48m · 11 videos
  • Premium skill.SQL Query Fundamentals53m · 11 videos
  • Premium skill.Managing Data in SQL Tables46m · 11 videos
  • Premium skill.Updating and Deleting Data in SQL54m · 11 videos
  • Premium skill.SQL Relationships and Joins56m · 13 videos
  • Premium skill.Aggregates and Grouping in SQL53m · 11 videos
  • Premium skill.SQL Subqueries45m · 11 videos
  • Premium skill.SQL Transactions and Rollbacks50m · 11 videos
  • Premium skill.Object-Oriented Programming For Data Analysts46m · 9 videos
  • Premium skill.PEP Guidelines For Data Analysts50m · 11 videos
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Certification

Certified Associate Data Analyst with Python

The PCAD certification validates practical junior-to-intermediate data analysis skills using Python and SQL across the full data analysis cycle, from acquisition and cleaning through modeling and communicating insights. It is aimed at junior data ana...

Exam PCAD-31-02Level AssociateDifficulty IntermediateCost $195
Data acquisition and pre-processingProgramming and database skillsStatistical analysisData analysis and modelingData communication and visualizationPython scripting best practices
Official certification page

Put this course to work for your team

Every plan includes this course plus the full library, virtual labs, and practice exams — or talk it through with sales.

For IT leaders

What IT leaders need to know before assigning this course

Organizations that rely on spreadsheets or one-off scripts often get inconsistent reporting, slow analysis, and higher risk from unclean or misunderstood data. This intermediate PCAD™ course gives IT Directors and Training Managers a structured way to build a shared Python data analysis baseline across analysts, data-focused IT Practitioners, and Team Leads who support reporting or analytics workflows.

The course is a substantial assignment: 61 skills and about 48.9 hours per learner. Plan it as a multi-week enablement path rather than a quick certification cram. Teams should already have some Python exposure before starting, then progress through Jupyter Notebooks, NumPy, Pandas, data cleaning, grouping, visualization, web scraping, SQL basics, OOP, descriptive statistics, and introductory machine learning evaluation.

For change management, assign by role or sprint: data preparation first, visualization second, then SQL, scraping, and model evaluation as needed. CBT Nuggets Playlists and Team Reporting can help Team Leads sequence the rollout and track completion across the full path.

Team Impact

How this training helps your team succeed

IT teams complete this training to make Python-based data work more repeatable, easier to review, and less dependent on a single specialist. The course connects practical analysis tasks with the tools teams are likely to use in day-to-day reporting and data exploration.

  • Clean and prepare datasets: Practitioners work with Pandas datasets, missing values, filtering, transforming, sorting, and grouping so reports are built on more reliable inputs.
  • Analyze structured data: Teams learn NumPy arrays, Pandas Series/DataFrames, descriptive statistics, and SQL basics for pulling and exploring structured data from databases or data warehouses.
  • Create clearer reporting outputs: Matplotlib and Seaborn skills support scatterplots, bar charts, pie charts, statistical visualizations, figures, and interactive widgets.
  • Expand data collection and evaluation: BeautifulSoup, CSS selectors, and XPath introduce web scraping, while K-nearest neighbor lessons show how to use training/test sets and read accuracy, precision, recall, F1 score, and support.

After completion

Capabilities your team walks away with

Knowledge

  • How Jupyter Notebooks support Python-based analysis workflows.
  • Core NumPy concepts, including multidimensional arrays, data types, operations, fancy indexing, broadcasting, and random number generation.
  • Pandas Series and DataFrame fundamentals for working with datasets.
  • Data cleaning concepts, including missing values, filtering, grouping, sorting, transformation, and applying functions.
  • Foundations of descriptive statistics, SQL for structured data, web scraping, visualization, OOP, and basic machine learning evaluation.

Ability

  • Build repeatable Python analysis workflows in notebooks.
  • Manipulate arrays and tabular datasets with NumPy and Pandas.
  • Prepare messy datasets for analysis by handling missing values and reshaping or filtering data.
  • Query structured data with SQL concepts and collect web data with BeautifulSoup, CSS selectors, and XPath.
  • Communicate findings with Matplotlib and Seaborn visualizations.
  • Evaluate simple classifier performance using training/test sets and metrics such as accuracy, precision, recall, F1 score, and support.

Readiness check

Confirm prerequisite knowledge before training begins

A short placement assessment on the CBT Nuggets assessments platform measures whether a learner already has the foundation this course assumes. IT Directors use it to put the right people in the right training — and any learner can take it right now to make sure they'll get full value from day one.

  • Questions generated from this course's own video transcripts — what gets measured is exactly what gets taught
  • Instant, per-learner results that show whether the prerequisite foundation is in place
  • Results roll up into team readiness reporting, so training hours go where they change outcomes
Runs on assessments.cbtnuggets.com — sign in with an Adept account so results roll up into team readiness reporting. Need one?
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