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Data Analysis and Visualization with Python · LearnSpace
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Data Analysis and Visualization with Python

Курс от Microsoft
Начальный≈ 21.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Description: This course delves into the world of data analysis with Python. You'll learn how to use libraries like pandas and Matplotlib to manipulate, analyze, and visualize data, extracting valuable insights and communicating findings effectively. Benefits: Become proficient in data analysis techniques, enabling you to extract meaningful insights from data and present them in compelling visualizations. By the end of this course, you'll be able to: • Perform data cleaning, transformation, and manipulation using pandas. • Create various types of visualizations using Matplotlib. • Understand the fundamentals of generative AI and its applications in data analysis. • Implement basic machine learning models for data analysis. Tools/Software: Python, Jupyter Notebook, pandas, Matplotlib, Scikit-learn This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.

Навыки, которые вы освоите

Model EvaluationData CleansingData QualityGenerative AIMachine LearningGenerative Adversarial Networks (GANs)Pandas (Python Package)MatplotlibData ManipulationExploratory Data AnalysisData AnalysisInteractive Data VisualizationData EthicsGenerative Model ArchitecturesData LiteracyData PresentationScientific VisualizationPlotlyPlot (Graphics)Data Visualization

Программа курса

5 модулей · 123 учебных материалов

01Introduction to data analysis23 материалов

Unveiling data analysis

Data analysis and visualization with Python syllabusЧтениеWhat is data analysis?ВидеоFoundations of data analysisЧтениеUnveiling Data AnalysisDIALOGUE

Учитесь у экспертов

Microsoft

Преподаватель курса

Data Analysis and Visualization with Python
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 21.9 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
The difference between data analysis and data scienceЧтение
The data analysis processВидео
Key concepts in data analysisЧтение
Data ethics and privacy: Navigating the responsible use of dataВидео
Data governanceВидео
Unveiling data analysisЗадание

Setting up your data analysis toolkit

Setting up your environment for data analysisВидеоJupyter notebook tips and tricksВидеоDemo: Jupyter notebook shortcuts and productivity tipsВидеоActivity: A simple analysis in Jupyter NotebookЗаданиеEssential Python libraries for data analysisЧтениеUse cases for Python librariesВидеоSetting up your data analysis toolkitЗадание

Diving into datasets

Understanding datasetsВидеоCommon dataset types and sourcesЧтениеFinding and accessing real-world datasetsВидеоData cleaning 101ЧтениеDiving into datasetsЗаданиеIntroduction to data analysisЗадание
02Data processing and manipulation24 материалов

pandas: Your data manipulation powerhouse

Manipulating data with pandasВидеоpandas Dataframes: The basicsВидеоpandas indexing explainedЧтениеDemo: Loading and inspecting datasets in pandasВидеоExploring data transformations through pandasВидеоpandas cheat sheetЧтениеDemo: Transforming data with pandasВидеоActivity: Loading and inspecting datasets in pandasЗаданиеpandas: Your data manipulation powerhouseЗадание

The hero of data analysis: Data cleaning

Exploratory data analysis (EDA)ВидеоThe importance of data cleaningВидеоEssential tactics for data manipulationЧтениеIdentifying and handling missing dataВидеоHandling duplicate values in datasetsВидеоCommon causes of missing dataЧтение

Using pandas for cleaning and exploration

Data types in Python: Choosing the right fitВидеоpandas for essential analysis tasksЧтениеDemo: pandas for exploration and cleaningВидеоTaming messy data with pandasВидеоUsing pandas for cleaning and explorationЗаданиеData processing and manipulationЗадание
03Data visualization24 материалов

Introduction to visualization

Charting your data visuallyВидеоWhat is data visualization?ЧтениеCommon visualizations toolsВидеоIntroduction to MatplotlibВидеоAnatomy of a Matplotlib PlotЧтениеMatplotlib galleryЧтениеIntroduction to visualizationЗадание

Creating visualizations

Explore visualization librariesВидеоChoosing the right visualization libraryЧтениеInteractive plots with PlotlyВидеоPlotly interactive dashboardsЧтениеCustomizing visualizations with BokehВидеоCreating visualizationsЗадание

Interpreting and presenting data insights

Use data for storytellingВидеоThe art of data storytellingВидеоApplication of data storytelling across industriesЧтениеPresenting data insightsВидеоData visualization best practicesЧтениеCognitive load theory and data visualizationЧтение
04Introduction to generative AI19 материалов

Basics of generative AI

What is generative AI?ВидеоGenerative AI vs. other AIЧтениеReal-world applications of generative AIВидеоThe ethics of AI-Generated contentВидеоEthical guidelines for generative AIЧтениеBasics of generative AIЗадание

Generating synthetic data with GenAI

Filling the gaps in your dataВидеоIntroduction to synthetic dataЧтениеUsing Generative Adversarial Networks (GANs)ВидеоSynthetic data generation techniquesЧтениеGenerating synthetic data with GenAIЗадание

Data augmentation

Data augmentation: Supercharging your datasetВидеоWhy augmentation mattersВидеоText augmentation techniquesВидеоImage augmentation techniquesЧтениеBest practices for data augmentationЧтениеData augmentationЗадание
05Introduction to machine learning33 материалов

Machine learning 101

What is machine learning?ВидеоHow machine learning worksВидеоKey terminology in machine learningЧтениеMachine learning in the real worldВидеоMachine learning 101Задание

Evaluating model performance

Why model evaluation mattersВидеоUnraveling the confusion matrixЧтениеBest practices for analyzing and presenting data setsЧтениеRegression metricsВидеоDemo: Using metrics for classificationВидеоRegression metrics for machine learningВидеоLinear regressionDIALOGUEBeyond the numbers: Interpreting evaluation metrics in contextЧтениеEvaluating model performanceЗадание

Building your first machine learning models

From data to predictions: The magic of machine learningВидеоWhat is a neural network in machine learning?ВидеоMachine learning basicsЧтениеDemo: Linear regression with Scikit-LearnВидеоClassification with logistic regressionВидеоScikit-Learn documentationЧтение

Leveraging synthetic data in machine learning

Synthetic data in ML: Case studiesВидеоDemo: Training and testing with synthetic dataВидеоSynthetic data: Balancing innovation and responsibilityВидеоEthical considerations of synthetic dataЧтениеLeveraging synthetic data in machine learningЗаданиеActivity: Analyzing and predicting customer churnПрограммирование
Detecting and removing outliers from datasetsВидео
The hero of data analysis: Data cleaningЗадание
Reviewing data processing and manipulationDIALOGUE
Avoid conclusion bias in data analysisВидео
Interpreting and presenting data insightsЗадание
Activity: Visualizing trendsЗадание
Telling the storyDIALOGUE
Data visualizationЗадание
Using GenAI in real lifeDIALOGUE
Introduction to generative AIЗадание
Your first machine learning model: A guideЧтение
Activity: Your first machine learning model implementationПрограммирование
Building your first machine learning modelsЗадание
Hands-on Activity: Presenting Data Visualizations to a Non-Technical ManagerDIALOGUE
Activity: Synthetic data generationЗадание
Introduction to machine learningЗадание
Data and visualization with Python: Pulling it all togetherЧтение