Data Protection Courses

Credential

Data Analytics in the Public Sector with R

121 ratings at Coursera

Equip yourself with R programming skills to analyze public sector data, informing policy decisions and administrative functions through data manipulation, visualization, and interpretation.

• Coursera
• 8 weeks, 10 hours/week
• Self-Paced
• Paid Course

Data Structures in C

73 ratings at Coursera

Learn to optimize memory usage, manage data efficiently, and create custom data types in C using pointers, arrays, and structures for improved programming skills.

• Coursera
• 15 hours 30 minutes
• Self-Paced
• Paid Course

Fundamentals of Data Analytics in the Public Sector with R

60 ratings at Coursera

Learn foundational R programming for public sector data analysis, covering key concepts, tidyverse libraries, and custom functions to analyze population and survey data effectively.

• Coursera
• 14 hours 42 minutes
• Self-Paced
• Paid Course

Credential

Total Data Quality

58 ratings at Coursera

Explore the Total Data Quality framework, focusing on evaluating and maximizing data quality before analysis. Learn essential steps for data collection, understanding sources, and improving quality in scientific investigations.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course

Credential

Understanding Data: Navigating Statistics, Science, and AI

56 ratings at Coursera

Develop data literacy skills to critically evaluate statistics, scientific research, and AI claims. Enhance decision-making abilities and learn to support perspectives with quality information.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

The Total Data Quality Framework

51 ratings at Coursera

Explore the Total Data Quality Framework, covering measurement, representation, and analysis dimensions. Learn to identify and mitigate threats to data quality in both designed and gathered data.

• Coursera
• 11 hours 59 minutes
• Self-Paced
• Paid Course

Prediction Models with Sports Data

42 ratings at Coursera

Learn to forecast sports game outcomes using Python, focusing on logistic regression modeling with team expenditure data. Apply and evaluate models for EPL, NBA, and NHL, exploring betting odds and analytics.

• Coursera
• 1 day 9 hours 28 minutes
• Self-Paced
• Paid Course

How to Describe Data

27 ratings at Coursera

Develop critical skills to evaluate and interpret data in everyday life, focusing on uncertainty, measurement, and statistical literacy without complex math.

• Coursera
• 9 hours 9 minutes
• Self-Paced
• Paid Course

AI-Powered Data Analysis: A Practical Introduction

23 ratings at Coursera

Explore AI-powered data analysis, from foundations to advanced techniques. Learn to leverage tools like ChatGPT for data acquisition, cleaning, visualization, and practical applications across various domains.

• Coursera
• 3 hours 58 minutes
• Self-Paced
• Paid Course

Politics and Ethics of Data Analytics in the Public Sector

18 ratings at Coursera

Explore ethical challenges in public sector data analytics, including bias and decision-making. Apply skills through a capstone project analyzing policy options using real-world data and RStudio.

• Coursera
• 14 hours 8 minutes
• Self-Paced
• Paid Course

Credential

Data-Oriented Python Programming and Debugging

18 ratings at Coursera

Master Python debugging with the OILER framework while learning data manipulation and analysis using NumPy, pandas, and SciPy libraries to produce high-quality, readable, and reproducible code for data science projects.

• Coursera
• 16 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 4 courses

Credential

More Applied Data Science with Python

19 ratings at Coursera

Master advanced Python data analysis techniques including data mining, clustering, network modeling, and information extraction using real-world datasets and machine learning libraries.

• Coursera
• 12 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

How Science Turns Data Into Knowledge

17 ratings at Coursera

Evaluate scientific claims, understand research methods, and interpret statistical results critically. Gain skills to analyze science news and develop a nuanced perspective on data and information.

• Coursera
• 11 hours 2 minutes
• Self-Paced
• Paid Course

NumPy and Pandas Basics for Future Data Scientists

13 ratings at Coursera

Master NumPy and pandas libraries for efficient data manipulation, from basic array operations to advanced techniques like broadcasting, reshaping, sorting, and joining arrays for numerical computing and data science.

• Coursera
• 19 hours 2 minutes
• Self-Paced
• Paid Course

Credential

Data Science for Health Research

13 ratings at Coursera

Learn to organize, visualize, and analyze health data using R for statistical modeling, linear regression, and logistic regression to make data-informed decisions in public health.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses