Why become a Certified Professional Data Analyst?
Employers increasingly look for data analysts with both academic backgrounds and industry recognised professional credentials that demonstrate practical, specialised industry knowledge. A recent study from Elucian found that over 85% of employers will expect employees to have professional credentials in addition to a degree qualification.
The Certified Professional Data Analyst (CPDA) credential is designed for practising data analytics professionals with a relevant first degree or equivalent from a recognised university, higher education institution or awarding body, together with a minimum of one year’s relevant professional experience.
The Certified Professional Data Analyst (CPDA) exam tests the key knowledge and skills required for the data analytics professional. It shows employers that holders of this credential are skilled in statistics and maths for data analysis, programming in R or Python, data management, data visualisation and predictive modelling. In addition, the certification demonstrates that a CPDA has proven professional experience and relevant academic education.
The Certified Professional Data Analyst (CPDA) credential is designed for practising data analytics professionals with a relevant first degree or equivalent from a recognised university, higher education institution or awarding body, together with a minimum of one year’s relevant professional experience.
The Certified Professional Data Analyst (CPDA) exam tests the key knowledge and skills required for the data analytics professional. It shows employers that holders of this credential are skilled in statistics and maths for data analysis, programming in R or Python, data management, data visualisation and predictive modelling. In addition, the certification demonstrates that a CPDA has proven professional experience and relevant academic education.
Degree
Credential
How the certification works?
In order to achieve the CPDA you must submit copies of academic qualifications from a recognised institution together with evidence of relevant professional experience and success in the CPDA professional exam.
CPDA overview
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Cost: €250
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Number of exam questions: 180
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Exam Duration : 3 hours
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Exam Pass Grade : 75%
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Minimum professional experience: 1 year
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Minimum education level: bachelor's degree or equivalent.
EXAM PREPARATION
How the CPDA exam works
The Certified Professional Data Analyst exam is a three hour online exam consisting of 180 questions that test the range of skills and knowledge required for data analytics professionals, including areas covered within the Edison European Data Science Framework’s body of knowledge (DS-BoK)
In order to prepare for the exam, candidates should be familiar with the CDPA exam specification and be able to answer questions in the format provided by the institute. Candidates may choose from either R or Python tracks for the exam
Once candidates register for the exam, they will be able to access the Data Science Institute’s assessment platform, where they can find practice questions, exam specifications and guidance.
Once candidates register for the exam, they will be able to access the Data Science Institute’s assessment platform, where they can find practice questions, exam specifications and guidance.
KNOWLEDGE AREAS COVERED
The exam covers the following areas
Descriptive statistics
Data visualisation
Business Intelligence Tools
SQL for Analytics
Statistical Inference
Hypothesis testing
Predictive modelling fundamentals
DESCRIPTIVE STATISTICS
Data Types
Measurement Scales
Measures of Central Tendency
Bivariate relationships
Python or R packages, functions and code for descriptive Statistics
Measurement Scales
Measures of Central Tendency
Bivariate relationships
Python or R packages, functions and code for descriptive Statistics
DATA VISUALISATION
Basic graphs and charts
Advanced graphs and charts
Communicating effectively with data visualisations
R or Python packages functions and code for data visualisation
Advanced graphs and charts
Communicating effectively with data visualisations
R or Python packages functions and code for data visualisation
STATISTICAL INFERENCE
Statistics terminology
Hypothesis testing
Analysis of Variance
Parametic tests
Non-parametric tests
R or Python packages functions and code for statistical analysis
Hypothesis testing
Analysis of Variance
Parametic tests
Non-parametric tests
R or Python packages functions and code for statistical analysis
HYPOTHESIS TESTING
Write R or Python programs that evaluate appropriate hypothesis tests
Draw statistical inference using output in R
Translate research problems into statistical hypotheses
Assess the most appropriate statistical test for a hypothesis
PREDICTIVE MODELLING FUNDAMENTALS
Model building process
Linear Regression
Model Validation
Multicollinearity
Python or R packages functions and code for predictive modelling
Linear Regression
Model Validation
Multicollinearity
Python or R packages functions and code for predictive modelling
BUSINESS INTELLIGENCE TOOLS
Excel functions for data analysis
Data Analytics Toolkit
Data Visualisation with Power BI
Dashboards
Data Visualisation with Power BI
Dashboards
SQL FOR ANALYTICS
SQL fundamentals
Connect R and Python to SQL
Data Management of large data sets
Data wrangling
Steps to become a certified Data Analyst
1
Apply
2
Study
3
Take Exam
4
Certification
1
Apply
Complete the certification application and submit copies of your certificates and resume. Once you receive confirmation of your eligibility you may pay your exam fee.
2
Study and Practice
Study for the certification exam using the guidance and practice questions on the Data Science Institute’s exam preparation portal.
3
Take the Exam
Take the exam. You need to achieve a minimum score of 75% to be certified
4
Certification
You will receive your verified digital certificate instantly on passing the exam
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