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Learn Data Cleaning, earn certificates with free online courses from Harvard, University of Michigan, Johns Hopkins, Duke and other top universities around the world. Read reviews to decide if a class is right for you.
Learn Python-based data analysis using Numpy, Pandas, and visualization libraries. Covers data cleaning, manipulation, and visualization techniques for extracting insights from various data sources.
Develop skills in digital research and visualization techniques across subjects and fields within the humanities.
Data Scientists spend most of their time cleaning data. In this course, you will learn to convert and manipulate messy data to extract what you need.
Master SQL for data analysis, enabling insight-driven decision-making. Learn core commands, advanced techniques, and database management to extract valuable insights from stored data.
Learn text mining and manipulation in Python, covering NLTK, regex, text cleaning, classification, and topic modeling for advanced document analysis.
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.
En este curso pondremos en práctica el potencial que nos ofrece el lenguaje R para darle solución a diversos problemas de los negocios actuales. Desarrollarás diversos proyectos que te permitan formar a tu primer portafolio de proyectos relacionados con…
Learn how to prepare data to ensure the efficacy of your analysis while improving fluency in Alteryx.
Data wrangling is a set of processes for turning raw and messy data into a clean format to answer interesting questions from the data. In this course, you will learn the three phases of data wrangling: gathering, assessing, and cleaning data.
Learn to build efficient, reproducible machine learning pipelines using MLflow, pytest, and Weights & Biases. Master data validation, experiment tracking, and model deployment for real-world ML projects.
Learn to prepare, clean, and model data effectively using Power Query and Power BI. Master relational data concepts, DAX language, and create efficient data models for analysis.
Master Python-based data science essentials, from NumPy and Pandas to machine learning, through hands-on projects with real datasets like Titanic and airline data. Build practical skills in visualization, preprocessing, and predictive modeling.
Master Python-based data analysis fundamentals through hands-on practice with libraries like NumPy and Pandas, from cleaning and preprocessing to statistical analysis and creating compelling visualizations.
Master data analysis fundamentals using R, from data manipulation and cleaning to statistical testing and visualization with ggplot2. Create compelling insights through hands-on practice with real datasets.
Master essential data manipulation and analysis using NumPy for numerical computing and Pandas for data wrangling, from basic array operations to advanced transformations and complex data analysis techniques.
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