Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Offert par
IBMÀ propos de ce cours
579 275 consultations récentes
Résultats de carrière des étudiants
14%
ont commencé une nouvelle carrière après avoir terminé ce cours
19%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Approx. 14 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Turc, Anglais, Espagnol, Persan
Ce que vous allez apprendre
Describe Python data acquisition and analysis techniques.
Analyze Python data using a dataset.
Identify three Python libraries and describe their uses.
Read data using Python's Pandas package.
Compétences que vous acquerrez
Predictive ModellingPython ProgrammingData AnalysisData Visualization (DataViz)Model Selection
Résultats de carrière des étudiants
14%
ont commencé une nouvelle carrière après avoir terminé ce cours
19%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Approx. 14 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Turc, Anglais, Espagnol, Persan
Offert par
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Programme du cours : ce que vous apprendrez dans ce cours
2 heures pour terminer
Importing Datasets
In this module, you will learn how to understand data and learn about how to use the libraries in Python to help you import data from multiple sources. You will then learn how to perform some basic tasks to start exploring and analyzing the imported data set.
2 heures pour terminer
6 vidéos (Total 20 min), 1 lecture, 6 quiz
2 heures pour terminer
Data Wrangling
In this module, you will learn how to perform some fundamental data wrangling tasks that, together, form the pre-processing phase of data analysis. These tasks include handling missing values in data, formatting data to standardize it and make it consistent, normalizing data, grouping data values into bins, and converting categorical variables into numerical quantitative variables.
2 heures pour terminer
6 vidéos (Total 19 min), 1 lecture, 6 quiz
2 heures pour terminer
Exploratory Data Analysis
In this module, you will learn what is meant by exploratory data analysis, and you will learn how to perform computations on the data to calculate basic descriptive statistical information, such as mean, median, mode, and quartile values, and use that information to better understand the distribution of the data. You will learn about putting your data into groups to help you visualize the data better, you will learn how to use the Pearson correlation method to compare two continuous numerical variables, and you will learn how to use the Chi-square test to find the association between two categorical variables and how to interpret them.
2 heures pour terminer
6 vidéos (Total 20 min), 1 lecture, 6 quiz
2 heures pour terminer
Model Development
In this module, you will learn how to define the explanatory variable and the response variable and understand the differences between the simple linear regression and multiple linear regression models. You will learn how to evaluate a model using visualization and learn about polynomial regression and pipelines. You will also learn how to interpret and use the R-squared and the mean square error measures to perform in-sample evaluations to numerically evaluate our model. And lastly, you will learn about prediction and decision making when determining if our model is correct.
2 heures pour terminer
6 vidéos (Total 27 min), 1 lecture, 6 quiz
Avis
Meilleurs avis pour ANALYSE DES DONNÉES AVEC PYTHON
par SC5 mai 2020
I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.
par RP19 avr. 2019
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
par HS29 juil. 2020
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently.overall best course in making anyone eager to learn from basics to handle advances with ease.
par AB12 févr. 2020
Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.
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