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Python for Data Science (and Version Control with GitHub) · LearnSpace
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Python for Data Science (and Version Control with GitHub)

Курс от Coursera
Начальный≈ 38 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Master Python programming for data analysis in this comprehensive course designed for aspiring data scientists. Through hands-on projects using real-world datasets, you'll learn essential data manipulation, visualization, and statistical analysis techniques while integrating modern AI tools and version control practices. This course is perfect for analysts and professionals who want to advance beyond spreadsheets to powerful programming solutions. Starting with Python fundamentals and progressing through advanced analysis techniques, you'll develop practical skills that directly apply to real-world data challenges. Upon completion, you'll be able to: • Import, clean, and manipulate data using Python's powerful libraries (Pandas, NumPy) • Create compelling visualizations with Matplotlib, Seaborn, and Plotly • Perform statistical analysis and A/B testing for data-driven decisions • Automate data workflows and generate professional reports • Implement version control best practices using GitHub

Навыки, которые вы освоите

GitHubPlotlyVersion ControlGit (Version Control System)Data ProcessingMatplotlibPandas (Python Package)A/B TestingStatistical Hypothesis TestingData ManipulationScientific VisualizationCollaborative SoftwareNumPyAI WorkflowsData ScienceData AnalysisPython ProgrammingStatistical MethodsStatistical AnalysisData Visualization

Программа курса

6 модулей · 76 учебных материалов

01Introduction to Python and Environment Setup20 материалов

Lesson 1: Welcome and Course Overview

Welcome to Python for Data ScienceВидеоCourse Syllabus & RoadmapЧтениеDay in the Life - An Interview With an ExpertВидеоEngageMetrics IntroductionЧтение

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Professionals from the Industry

Преподаватель курса

Python for Data Science (and Version Control with GitHub)
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Обучение на Coursera

≈ 38 ч

6 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, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
Video Transcript AccessЧтение
Your Data Science JourneyDIALOGUE

Lesson 2: Python Fundamentals & Jupyter Notebook Setup

Introduction to Jupyter Notebook with Python: Overview and ResourcesЧтениеPython BasicsЧтениеHello, Python!ЧтениеGetting Started with Jupyter NotebooksВидеоJupyter Notebook Setup & BasicsЛабораторнаяCase Study: Data Environments in IndustryЧтениеPython and Jupyter Notebook DynamicsDIALOGUEKnowledge Check: Python Syntax & Notebook BasicsЗадание

Lesson 3: GitHub for Data Science Projects

Version Control Best PracticesЧтениеFamiliarize with Git and GitHubЧтениеGit Basics for Data ScientistsЧтениеVersion Control in ActionDIALOGUE

Lesson 4: Apply Foundational Skills in a Practical Challenge

Initial Setup and Version Control ChallengeЛабораторнаяGraded Assessment: Environment Setup and GitHubЗадание
02Data Loading and Manipulation13 материалов

Lesson 1: Data Loading Techniques

Data Import Essentials: CSV, Excel, and APIsВидеоData Import LabЛабораторнаяKnowledge Check: Data Import Functions Задание

Lesson 2: Data Manipulation with Pandas

Transforming HR Data with PandasВидеоDataFrame Operations LabЛабораторнаяPandas Recap and Comparison to ExcelDIALOGUE

Lesson 3: Handling Categorical and Date/Time Data

Python Data Transformation EssentialsВидеоData Type Transformation LabЛабораторнаяKnowledge Check: Non-numeric Data HandlingЗадание

Lesson 4: Numerical Operations with NumPy

NumPy Speed Boost: From Loops to Lightning-Fast ArraysВидеоNumerical Calculations LabЛабораторнаяNumPy Recap and ApplicationsDIALOGUE

Lesson 5: Integrate Techniques in a Hands‑on Challenge

Graded Lab: Multi-Source Data Integration ChallengeПрограммирование
03Data Exploration and Visualization13 материалов

Lesson 1: Exploratory Data Analysis (EDA)

Exploratory Data Analysis TechniquesЧтениеFirst Look: Smart EDA for HR Data ВидеоGuided EDA Exercises LabЛабораторнаяKnowledge Check: EDA Concepts Задание

Lesson 2: Data Visualization with Matplotlib and Seaborn

Choosing the Right Visualization: A Guide to Basic Chart TypesЧтениеProfessional Visualizations: From Basic to BeautifulВидеоBuilding Visualizations LabЛабораторнаяVisualization Customization and Chart SelectionDIALOGUE

Lesson 3: Interactive Visualizations with Plotly

Interactive Dashboards with Plotly: Bringing Data to LifeВидеоInteractive Visualization LabЛабораторнаяRefining Interactive VisualizationsDIALOGUE

Lesson 4: Synthesize Insights in a Challenge Scenario

Graded Lab: Comprehensive EDA ChallengeПрограммированиеGraded Assessment: Visualization Challenge Задание
04Advanced Data Analysis Techniques14 материалов

Lesson 1: Statistical Analysis in Python

Statistical Methods in PythonЧтениеStatistical Analysis in HR: From Hypothesis to InsightsВидеоInterpreting Statistical ResultsDIALOGUEStatistical Analysis LabЛабораторная

Lesson 2: A/B Testing with Python

A/B Testing in Action: Training Methods AnalysisЧтениеA/B Testing in Action: Analyzing Department PerformanceВидеоA/B Testing Strategy and AnalysisDIALOGUEA/B Testing LabЛабораторная

Lesson 3: Automation, Documentation, and Reporting

Automating Your Data Science WorkflowВидеоDocumenting Your Code EffectivelyDIALOGUEAutomation & Reporting LabЛабораторная

Lesson 4: Demonstrate Advanced Skills Through a Challenge

Integrated Statistical Analysis and A/B Test ChallengeЛабораторнаяGraded Assessment: Advanced Data AnalysisЗаданиеData Science Skills in ActionDIALOGUE
05GitHub Integration 10 материалов

Lesson 1: Version Control and Notebook Management with GitHub

Versioning Your Notebooks with GitHubВидеоGitHub Integration LabЛабораторнаяKnowledge Check: GitHub Version ControlЗадание

Lesson 2: Documentation with Generative AI

Automated Documentation TechniquesЧтениеLeveraging AI for Better Documentation ВидеоAI-Assisted Documentation LabЛабораторная

Lesson 3: Managing Experimentation & Branching Strategies in Data Science

Branching Strategies for Data Science ProjectsВидеоExperiment Management LabЛабораторнаяOptimizing Your Git WorkflowDIALOGUEGraded Assessment: GitHub Integration and Version ControlЗадание
06Data Science Workflow Capstone6 материалов

Lesson 1: Capstone Introduction & Project Setup

Industry Expert Interview on Data Science WorkflowsВидеоIntroducing TrendWave Media: Your Capstone Project DatasetЧтениеCapstone Project OverviewЧтение

Lesson 2: Capstone Implementation & Assessment

Capstone Project LabЛабораторнаяGraded Assessment: End-of-Course AssessmentЗаданиеCourse Wrap-UpЧтение