Data Management Courses

Data Analysis with Python Project

Comprehensive exploration of data analysis techniques, from classification to outlier detection, empowering learners to conduct real-world projects and make data-driven decisions.

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

Integral Calculus and Numerical Analysis for Data Science

109 ratings at Coursera

Intuitive approach to integral calculus and numerical analysis, covering integration, root-finding, matrix decomposition, and partial derivatives for data science applications.

• Coursera
• 3 hours 32 minutes
• Self-Paced
• Paid Course

Microcredential

Software Architecture for Big Data

106 ratings at Coursera

Learn principles and patterns for architecting large-scale distributed systems that handle big data. Gain industry insights on building performant software for data-intensive applications.

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

Fundamentals of Software Architecture for Big Data

91 ratings at Coursera

Aprende a construir y escalar sistemas distribuidos intensivos en datos, aplicando prácticas de ingeniería de software y microservicios. Ideal para profesionales y graduados recientes en ciencia de datos o informática.

• Coursera
• 20 hours 29 minutes
• Self-Paced
• Paid Course

Statistical Estimation for Data Science and AI

90 ratings at Coursera

Learn statistical inference, sampling distributions, and confidence intervals. Explore estimation methods, construct good estimators, and develop confidence intervals for various settings. Gain practical skills for data analysis and interpretation.

• Coursera
• 1 day 5 hours 23 minutes
• Self-Paced
• Paid Course

Data Processing and Manipulation

Learn essential data processing techniques: handling missing values, detecting outliers, sampling, dimension reduction, scaling, discretization, and using data cubes and pivot tables for efficient analysis and decision-making.

• Coursera
• 1 day 4 hours 43 minutes
• Self-Paced
• Paid Course

Data Acquisition, Risk, and Estimation

Learn data acquisition planning, estimation techniques, and risk reduction for capital investments using sampling, hypothesis testing, and ROI calculations.

• Coursera
• 9 hours 7 minutes
• Self-Paced
• Paid Course

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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Paid Course
• 3 courses

Systems Engineering and Program Management

57 ratings at Coursera

Learn to apply Systems Engineering to complex program management, including risk assessment, scope definition, and change control, while developing essential leadership skills for engineering and technical roles.

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

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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Paid Course