
Python Data Analyst Certification Exam PCED-30-02 (2026)
About this course
Now is the time to get certified as Data Analyst with Python!Python Institute PCED-30-02: Certified Entry-Level Data Analyst with PythonThere are six Practice Tests with preparation questions from all knowledge areasto prepare for the PCED-30-02 exams at the Python Institute.The first Practice Test should be worked through in Practice Mode.The other five Practice Tests should be taken in Exam Mode.They have the same number of questions as the official exam.You will have 40 questions and 60 minutes.Every question has an explanation and/or a Try-It-Yourself-Codewhich you can run to better understand the topic.You can download the Try-It-Yourself-Code for all questions.(The download link will be in your welcome message.)Why learn Data Analysis with Python?Data analysis has become one of the most valuable skills in today's job market, and Python is the leading programming language for data work. Here's why learning data analysis with Python is a smart investment in your career:1. Python Is the Industry StandardPython dominates the data analysis field.
Major companies like Google, Facebook, Amazon, and Netflix use Python for data-driven decisions. Learning Python means learning the language that professionals actually use every day.2. Powerful, Easy-to-Learn LibrariesPython offers specialized libraries that make data analysis fast and intuitive:- Pandas for data manipulation and cleaning- NumPy for numerical computations- Matplotlib and Seaborn for data visualization- Jupyter Notebooks for interactive analysisYou don't need to rebuild everything from scratch—these tools let you focus on insights, not infrastructure.3.
High Demand, Strong SalariesData analysts are in demand across every industry: finance, healthcare, e-commerce, marketing, and more. According to job market reports, data analyst positions consistently rank among the fastest-growing roles, with competitive salaries worldwide.4. Entry-Level FriendlyUnlike many programming paths, data analysis with Python is accessible to beginners.
You don't need a computer science degree. With the right training, you can go from zero to job-ready in months, not years.5. Real-World ImpactData analysis turns raw numbers into actionable insights.
You'll learn to:- Identify trends and patterns- Create compelling visualizations- Support business decisions with evidence- Tell stories with data6. Future-Proof SkillAs AI and automation grow, the ability to work with data becomes even more critical. Python is also the primary language for machine learning and AI, so your skills will scale as you advance.By mastering data analysis with Python, you're not just learning a tool—you're building a career foundation that opens doors across industries, with room to grow into data science, machine learning, and beyond.Exam Syllabus:Introduction to Data and Data Analysis Concepts:Define and Classify DataDescribe Data Sources, Collection Methods, and StorageExplain the Data Lifecycle and Its ManagementUnderstand the Scope of Data Science, Analytics, and AnalysisIdentify key questions each type answers and their business relevance.Python Basics for Data Analysis:Work with Variables and Data TypesUse Python Data Collections and SequencesUse Functions and Handle ExceptionsControl Program Flow with Conditionals and LoopsUse Modules and PackagesWorking with Data and Performing Simple Analyses:Read and Write Data Using FilesClean and Prepare Data for AnalysisPerform Basic Analytical ComputationsConduct Basic Exploratory Data Analysis (EDA)Communicating Insights and Reporting:Understand Basic Principles of Data VisualizationApply Fundamentals of Data StorytellingCreate Clear and Concise Analytical ReportsCommunicate Insights Effectively in Presentations
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Course Information
Level: All Levels
Suitable for learners at this level
Duration: Self-paced
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Instructor: Cord Mählmann
Expert course creator
This course includes:
- 📹Video lectures
- 📄Downloadable resources
- 📱Mobile & desktop access
- 🎓Certificate of completion
- ♾️Lifetime access
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