Zurück zu Datenanalyse mit Python

Sterne

14,024 Bewertungen

•

2,080 Bewertungen

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!
Topics covered:
1) Importing Datasets
2) Cleaning the Data
3) Data frame manipulation
4) Summarizing the Data
5) Building machine learning Regression models
6) Building data pipelines
Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts:
Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

SC

5. 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.

RP

19. Apr. 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.

Filtern nach:

von Ram K

•7. Mai 2020

Initial part of course was easy, but the labs proved more and more useful. As I learned the course, I applied the charting skills directly to work, and was able to use Pandas to combine data from 3 databases, evaluate and report on the data to my company. It is already making a difference in our ability to make better data driven decisions every day.

von Mona A

•17. Juni 2019

Great Course! I got a great insight into multiple steps involved in data analysis using python starting from an initial data set to pre-processing it, exploratory analysis, doing multiple operations to create possible models and ways to evaluate the models. I hope to be able to use them to solve some sample data sets and come up with possible models

von Volodymyr C

•23. Juni 2019

Did this after Andrew Ng's Machine Learning to learn to do the same things in Python. Great course for people somewhat familiar with Python basics (I used datacamp to get a feel for Python and methods etc. first). Labs were really good for reinforcing knowledge from quizzes and videos. Overall, very nice course - will recommend to others!

von Ramjan

•19. Dez. 2018

This is my first course that i completed, and i am very glad to do this .

thanking you for giving me this opportunity to enrolled this course

i learned a lot of new things from this course this was very fruitful for me.

the slides was nicely represented and the way of teaching was so amazing

i am very very thankful to all the Coursera Team

von Penchalaiah G

•7. Aug. 2019

This course is very use for regression model end to end scratch of evaluation and easily understand the coding theory explanation but ridge regression is somewhat improvement is needed.

Finally, I suggested to this course for learning data analysis with python.

Thanks for wonder full opportunity to learn this course in course-era team...

von Muhammad Y

•7. Okt. 2018

This course is probably the most concise and well explained course I have ever taken on the subject. Materials are explained very well, and in a concise manner. The only downside is that the assessment for this course is based on quizzes, which are way too easy. Nevertheless, the course contains ungraded labs which are really useful.

von Mihailo P

•12. Apr. 2020

This is the most complex course in the IBM Data Specialization Curriculum until now. There is a lot to cover and I would advise the students to go through the notebooks for practice 2 times to make sure to remember everything. One thing that is a bit confusing are functions for creating plots as we did not cover them in details yet.

von Rohit B

•16. März 2020

Awesome course on gaining Python skills for performing structured data analyses. If you are already attending the IBM Data Science certification, this course is a "step up" from the initial courses to bring a lot of things together. I would highly recommend doing it in the recommended order, else the learning curve may be too steep.

von Diderico v E

•2. Feb. 2020

Wow! Excellent course that provides a great skills-focused overview on how to do data analysis with Python. The videos are first-rate, high quality and summarize the essential points nicely. The data set is real and it is used throughout the course and that helps understand the different features of data analysis taught by pandas.

von Stuart S

•2. Apr. 2020

Great introduction for using Python for data analysis. I found the segments on using Pandas, scikitlearn, and Matplotlib, particularly useful. Also, the labs' use of Jupyter notebooks, were excellent, because of the ability to introduce new variables or other data, and to see how it affects the outcome. Thank you very much!

von Dongre O

•2. Mai 2020

This course gave me very good understanding on basic concepts in Data Science and how we can make use of python. I would recommend this course to people who are searching for basics of data science. If you are from programmer then you will be able to correlate software development life cycle and Data Science Development.

von Mmr R

•27. Mai 2019

It was really helpful for me. Now i can clearly explain what is data. How we can explore data from a big data-set, How we can analyze different type of data-set. I am so much happy with this course. Now i will try to use this technique in my next steps. Special thanks Coursera community for creating this opportunity.

von David A

•16. Okt. 2019

Very useful analytical techniques were learned such as cleaning the data, multiple linear regression, and working with test and training data. This course gave me a good foundation on the approach to analyze large databases. I also feel this will help in learning R because I now know the analytical process.

von Mayank S

•12. Juni 2021

Trust me! This is best course for beginners, This is how it should be taught. No previous coding experience needed, even mathematics used is explained clearly. Making notes will help you in future while writing codes. After this course, you can confidently move to other courses of IBM Data specialization.

von Aakanksha R

•20. Sep. 2020

It is a really well-planned and informative course. The labs provided after every chapter are indeed a lot helpful to understand, recollect and visualize what we learnt during theory lectures. I would recommend this course to all as I found it helpful to improve my Data Analysis & Visualization skills.

von Meenakshi S A

•20. Nov. 2019

It was a very interesting and correctly paced course for learning Data Analysis with Python. The course content and the assignments were very helpful in understanding the course well. Will recommend this course to all who want to do a well paced introductory course on Data Analytics using Python

von Md. R H

•22. Sep. 2019

This course is outstanding valuable for the beginners who wants to build their career as data analysist. I have learned a lots of valuable statistical and progrmming for data analysis. Thanks to all instructor to give us such a opportunity to learn such kind of code and method for data analysis.

von Marta F d O F d N N

•2. Juni 2020

This was a great introductory course to statistical modeling with Python. I learned a lot of the basic methods to perform linear regression models and to describe statistical variables. The final assignment was slightly challenging, but doable if you follow the labs. All and all a great course!

von Jamiil T A

•1. Jan. 2019

Awesome. A must take course very handy at giving the foundation of data analysis with python and what a nice introduction to linear regression with the library sklearn. For more it looks more like an in-depth course in linear regression. Kudos, the explanations of concepts were well approached.

von Alpesh G

•11. Aug. 2021

This course starts with Importing the dataset in Jupyter Notebook, followed by Data Wrangling, Exploratory Data Analysis, Model Development and Model Evaluation, and end with the final assessment applying all the concepts learned.

Thanks to IBM and Coursera for this great learning experience.

von Viren B

•31. Mai 2021

the course is too good to be true! it is an elaborate explanation of all the terms with the logic behind it. Seamless experience with the inbuilt code writing lab. I would highly recommend it to all who are at the doorstep of data analysis. This is the first step towards it, and a mighty one!

von Md. A A J

•2. Mai 2020

The hands on examples for practicing on IBM cognitive lab, videos and lecturers made are great and helpful. The course contents are clear, precise and lecturer is very knowledgeable.

Joining and getting help from course mates and moderates in discussion forum is Excellent!

Ashfaque A. Joarder

_{}^{}

von Gregory J O C

•27. Juni 2020

I loved this course!

Though, for a beginner like me, it can be kind of confusing to be shown things that are not covered in the course (i.e, plots in which a lot of characteristics have to be set...), this tends to happen in labs.

But for the rest, everything was crystal clear!

Best wishes!

von Konstantin D

•22. Feb. 2019

The first "week" was way too simple. I believe things like "what a file path is" should belong to another course. The last 4 "weeks" gave a good picture of where to start with data analysis. The whole course can be completed after 5-10 hours (depends how long you play with the dev tool).

von Sumanta S

•9. Sep. 2020

This course builds your fundamentals of data analysis ,from how to load data to data cleaning, removing missing values, data interpretation, building models, testing them using pipleine to check if model gives proper output , splitting data sets as test set and for model learning. etc

- Google Data Analyst
- Google-Projektmanagement
- Google-UX-Design
- Google IT-Support
- IBM Datenverarbeitung
- IBM Data Analyst
- IBM-Datenanalyse mit Excel und R
- IBM Cybersecurity Analyst
- Facebook Social Media Marketing
- IBM Full Stack-Cloudentwickler
- Salesforce Sales Development Representative
- Sales Operations in Salesforce
- Soporte de Tecnologías de la Información de Google
- Certificado profesional de Suporte em TI do Google
- Google IT Automation with Python
- DeepLearning.AI TensorFlow
- Beliebte Zertifizierungen für Cybersicherheit
- Beliebte SQL-Zertifizierungen
- Beliebte IT-Zertifizierungen
- Alle Zertifikate anzeigen

- Kostenlose Kurse
- Lernen Sie eine Sprache
- Python
- Java
- Webdesign
- SQL
- Gratiskurse
- Microsoft Excel
- Projektmanagement
- Cybersicherheit
- Personalwesen
- Kostenlose Kurse in Datenverarbeitung
- Englisch sprechen
- Inhalte verfassen
- Full-Stack-Webentwicklung
- Künstliche Intelligenz
- C-Programmierung
- Kommunikationsfähigkeiten
- Blockchain
- Alle Kurse anzeigen

- Kompetenzen für Datenwissenschaftsteams
- Datengestützte Entscheidungsfindung
- Kompetenzen im Bereich Software Engineering
- Soft Skills für Ingenieurteams
- Management-Kompetenzen
- Marketing-Kompetenzen
- Kompetenzen für Vertriebsteams
- Produktmanager-Kompetenzen
- Kompetenzen im Bereich Finanzen
- Android-Entwicklungsprojekte
- TensorFlow- und Keras-Projekte
- Python für alle
- Deep Learning
- Excel-Kenntnisse für Beruf
- Geschäftsgründungen
- Maschinelles Lernen
- AWS-Grundlagen
- Datenengineering-Grundlagen
- Datenanalysefähigkeiten
- Kompetenzen für UX-Designer

- MasterTrack® Certificates
- Zertifikate über berufliche Qualifikation
- Universitätszertifikate
- MBA- und Business-Abschlüsse
- Abschlüsse in Data Science
- Abschlüsse in Informatik
- Abschlüsse in Datenanalyse
- Abschlüsse im Gesundheitswesen
- Abschlüsse in Sozialwissenschaften
- Management-Abschlüsse
- Abschlüsse von europäischen Spitzenuniversitäten
- Masterabschlüsse
- Bachelorabschlüsse
- Studiengänge mit Performance Pathway
- BSc-Kurse
- Was ist ein Bachelorabschluss?
- Wie lange dauert ein Masterstudium?
- Lohnt sich ein Online-MBA?
- 7 Finanzierungsmöglichkeiten für die Graduate School
- Alle Abschlüsse anzeigen