К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
Data Science with Python · LearnSpace
Назад в каталог
courseraIT и технологии

Data Science with Python

Курс от Packt
Средний≈ 11.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive Data Science with Python course, you will master essential libraries such as NumPy, Pandas, Matplotlib, and PyTorch to solve real-world data science challenges. Starting with NumPy, you’ll learn how to work with arrays, perform linear algebra, and manipulate large datasets. You’ll then explore Pandas to filter, analyze, and visualize data efficiently, followed by Matplotlib for creating informative plots and visualizations that uncover patterns in data. As you progress, you will dive into advanced image processing techniques with Matplotlib, build interactive plots using Plotly, and gain hands-on experience with PyTorch fundamentals. The course will guide you through essential concepts like tensors, GPU acceleration, broadcasting, and model training, offering a solid foundation for machine learning and deep learning tasks. Designed for individuals eager to advance their data science skills, this course is ideal for beginners and intermediate learners. With practical exercises, real-world applications, and interactive lessons, you'll be prepared to tackle any data science project. Upon completion, you'll be ready to take your skills further in the field of machine learning and artificial intelligence. By the end of the course, you will be able to manipulate data with NumPy and Pandas, visualize data using Matplotlib and Plotly, process images, and implement machine learning models using PyTorch.

Навыки, которые вы освоите

NumPyMatplotlibPyTorch (Machine Learning Library)Data Visualization SoftwareScatter PlotsInteractive Data VisualizationPandas (Python Package)PlotlyLinear AlgebraDeep LearningData ManipulationData WranglingPlot (Graphics)Machine Learning MethodsNumerical AnalysisApplied Machine LearningPython ProgrammingImage Analysis

Программа курса

6 модулей · 84 учебных материалов

01NumPy15 материалов

NumPy

Introduction to the Course 'Data Science With Python'ЧтениеFull Specialization ResourcesЧтениеNumPy Arrays, Shape, and ReshapeВидеоNumPy Arrays of Zeros, Ones, and the Identity MatrixВидео

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса

Data Science with Python
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 11.9 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский

Часть программы вашего университета
Empty and RandomВидео
Indexing and Slicing in NumPyВидео
Arithmetic and NumPyВидео
Rough Idea of Linear Algebra and Its ApplicationsВидео
(Advanced) Concepts from Linear Algebra in NumPyВидео
Solving Linear SystemsВидео
Logic: Element-Wise ComparisonВидео
Logic: Comparison with ScalarsВидео
Logic: Filtering and WhereВидео
Fundamentals of NumPy Arrays and Linear Algebra OperationsDIALOGUE
NumPy - AssessmentЗадание
02Pandas10 материалов

Pandas

Getting Started with Pandas: Titanic Dataset AnalysisВидеоFilteringВидеоFiltering and the isin OperatorВидеоFilter Rows Using notnaВидеоExamples of Filters and LogicВидеоSolutions to the Filtering Exercises from the Previous LectureВидеоFiltering ColumnsВидеоApplying concat to Two SeriesВидеоFiltering and Concatenating DataFrames with Pandas: The Titanic DatasetDIALOGUEPandas - AssessmentЗадание
03Matplotlib, Graphing, and Statistics22 материалов

Matplotlib, Graphing, and Statistics

Simple Bar PlotВидеоBar Plot—Calories per DayВидеоBox PlotВидеоReal-World Scenario: Customer Satisfaction Analysis—Box PlotВидеоA Simple Scatter PlotВидеоScatter Plot Example—Average Daily Temperatures and Ice Cream SalesВидеоComparing Groups with Scatter PlotsВидеоGraphing a Function with Scatter PlotВидеоGraphing LinesВидеоText AnnotationsВидеоLinear RegressionВидеоHistogramsВидеоSubplotsВидеоMultiple Subplots with Different Colors and TitlesВидеоEnhancing Titles Using LaTeXВидеоImage SubplotsВидеоPie ChartВидеоStack PlotВидеоBar ChartВидео3D Plot Using a Mesh GridВидеоExploring Data Visualization with MatplotlibDIALOGUEMatplotlib, Graphing, and Statistics - AssessmentЗадание
04Matplotlib and Image Processing12 материалов

Matplotlib and Image Processing

Loading an RGB ImageВидеоExtracting RGB ChannelsВидеоConverting an RGB Image to GrayscaleВидеоExploring Color MapsВидеоCreating n by n RGB ImagesВидеоImage Manipulation—ThresholdingВидеоImage Manipulation—CompressionВидеоImage Manipulation—Squeeze ImageВидеоImage Manipulation—Inverting ImagesВидеоImage Manipulation—Image TilingВидеоImage Processing Fundamentals with Matplotlib and NumPyDIALOGUEMatplotlib and Image Processing - AssessmentЗадание
05Plotly and Interactive Plots8 материалов

Plotly and Interactive Plots

Interactive Line PlotВидеоLine Plot ModesВидеоInteractive Scatter Plot with TooltipsВидеоInteractive 3D Surface PlotВидеоFigures as DictionariesВидеоFigures as Graph ObjectsВидеоComparing Interactive Plots with Plotly and MatplotlibDIALOGUEPlotly and Interactive Plots - AssessmentЗадание
06PyTorch Fundamentals17 материалов

PyTorch Fundamentals

Google Colab and tqdmВидеоGetting HelpВидеоGetting More HelpВидеоIntroducing PyTorch and Tensors 1ВидеоIntroducing PyTorch and Tensors 2ВидеоUsing the GPUВидеоOperators and More OperationsВидеоIndexing and MaskingВидеоMasking ContinuedВидеоCloning TensorsВидеоBroadcasting—First StepsВидеоBroadcasting ContinuedВидеоMore Broadcasting ExamplesВидеоConclusion to the Course 'Data Science With Python'ЧтениеPyTorch Fundamentals - AssessmentЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание