Data Protection Courses

Python Packages for Data Science

78 ratings at Coursera

Explore essential Python packages for data science: Pandas, NumPy, Matplotlib, and Seaborn. Learn data manipulation and visualization techniques to enhance your data analysis skills.

• Coursera
• 20 hours
• On-Demand
• Paid Course

Data Mining Methods

71 ratings at Coursera

Explore core data mining techniques including pattern analysis, classification, clustering, and outlier analysis. Learn advanced methods for complex data and discover research frontiers in the field.

• Coursera
• 1 day 25 minutes
• On-Demand
• Paid Course

Data Wrangling with Python Project

Apply data wrangling techniques to transform raw data into a refined dataset ready for analysis. Gain hands-on experience in identifying sources, collecting, integrating, and processing data for real-world challenges.

• Coursera
• 1 day 1 hour 41 minutes
• On-Demand
• Paid Course

Microcredential

Statistical Modeling for Data Science Applications

60 ratings at Coursera

Develop advanced statistical modeling skills for data science, including linear regression, ANOVA, and generalized linear models, with practical applications using R programming.

• Coursera
• 12 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

Microcredential

Expressway to Data Science: R Programming and Tidyverse

56 ratings at Coursera

Master R programming and Tidyverse for data science: import, tidy, and visualize data using ggplot2. Develop skills for reproducible research and advanced data analysis techniques.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

Microcredential

Data Science Methods for Quality Improvement

53 ratings at Coursera

Gain data analysis skills for quality improvement in business and industry. Learn RStudio, RMarkdown, and techniques to enhance performance, quality, and reliability across various sectors.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

Statistical Inference and Hypothesis Testing in Data Science Applications

51 ratings at Coursera

Learn hypothesis testing for data science applications, covering theory, implementation, and ethical considerations. Develop skills to make informed decisions from data using statistical inference techniques.

• Coursera
• 1 day 12 hours 40 minutes
• On-Demand
• Paid Course

Ethical Issues in Data Science

49 ratings at Coursera

Explore ethical challenges in data science, including privacy, security, bias, and medical applications. Gain insights to navigate ethical considerations in your data science career.

• Coursera
• 23 hours 52 minutes
• On-Demand
• Paid Course

Microcredential

The Data Driven Manager

45 ratings at Coursera

Learn to understand, describe, and analyze data for informed decision-making. Develop skills in data visualization, probability, risk assessment, and problem-solving to drive business and engineering outcomes.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course

Microcredential

Statistics and Applied Data Analysis

46 ratings at Coursera

Master statistical concepts from basics through advanced analysis, using Excel and R for data visualization, hypothesis testing, and predictive modeling across three progressive levels.

• Coursera
• 12 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

Fundamentals of Data Visualization

41 ratings at Coursera

Explore data visualization design, development, and evaluation. Learn to create effective visualizations, use exploratory tools, and craft data narratives through hands-on experience with user-centered design and web-based techniques.

• Coursera
• 15 hours 3 minutes
• On-Demand
• Paid Course

Data Science as a Field

39 ratings at Coursera

Explore data science's evolution, applications, and methodologies. Learn about the data analysis process, pitfalls, and effective communication of results in various professional settings.

• Coursera
• 10 hours 56 minutes
• On-Demand
• Paid Course

Statistics and Data Analysis with Excel, Part 1

39 ratings at Coursera

Learn foundational statistics concepts and apply them using Excel. Covers descriptive statistics, probability, and probability distributions. Ideal for beginners in data science and analytics.

• Coursera
• 16 hours 31 minutes
• On-Demand
• Paid Course

Microcredential

Data Wrangling with Python

38 ratings at Coursera

Master essential data wrangling skills with Python, covering tools, collection, understanding, preprocessing, and visualization. Gain practical experience through exercises and a final project to tackle real-world data challenges.

• Coursera
• 8 weeks, 10 hours a week
• On-Demand
• Paid Course
• 5 courses

Managing, Describing, and Analyzing Data

34 ratings at Coursera

Learn to classify, visualize, and analyze data using R. Master descriptive statistics, probability distributions, sampling techniques, and hypothesis testing for informed decision-making and statistical inference.

• Coursera
• 17 hours 49 minutes
• On-Demand
• Paid Course