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Introduction to Python for Data Analytics
Nivå: Foundation
Snittbetyg:
4,52/5 Based on 44 Reviews
Gain the skills you need to analyse and visualise data with Python. In this Python training, you learn the fundamentals of Python programming with a focus on data analytics, and work with popular statistical computing libraries — like numPy, Pandas, sciPy, and Scikit-learn — that allow you to begin analysing data to answer key business questions.
Nyckelfunktioner:
- Attend online or bring this course to your facility
- After-course instructor coaching
Du kommer lära dig att:
- Use Python for statistical data analysis
- Generate summary statistics with pandas
- Clean, transform, and reshape data
- Glean insights from the data through visualisation
Välj den utbildningsform som passar dig bäst
FÖRETAGSINTERN UTBILDNING
Teamträning
- Använd denna eller någon annan utbildning i ditt företag
- Fullskalig programutveckling
- Levereras när, var och hur du vill
- Blandade utbildningsmodeller
- Skräddarsytt innehåll
- Coaching av ett expertteam
Anpassa kurs och innehåll efter teamets behov
Kontakta ossBLANDAT LÄRANDE
On Demand & Live Granskningssession
Unlimited annual access to:
- 12 eBooks
- 2 on-demand video courses
- 1-day instructor-led training course
Utveckla dig och ditt team med anpassade eller öppna kurser alternativt e-learning
Learning Tree erbjuder kundanpassad utbildning hos er, öppna kurser i Stockholm, London eller Washington, möjlighet att delta via våra Anywhere centers (Malmö, Göteborg, Linköping, Stockholm eller Borlänge) eller olika former av e-learning med lärarstöd. Läs mer på www.learningtree.se/priser .
Teamträning
On Demand & Live Granskningssession
Python for Data Analytics Training Information
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Data Science Blended Training Description
The eBooks and on-demand courses provided with this offering are a great way to explore your interest in the topics covered in the instructor-led course. At any time during your annual access to this offering, you may attend one of our 1-day review sessions, Course 4509: Introduction to Python for Data Analytics.
Course Outline & On-Demand Training Content
eBooks
- Managing Data Science
- Hands-On Data Analysis with Pandas
- Hands-On Python Natural Language Processing
- Data Science Algorithms in a Week - Second Edition
- Machine Learning for Algorithmic Trading - Second Edition
- Hands-On Neural Networks
- Mastering Machine Learning Algorithms - Second Edition
- Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits
- Hands-On Data Science for Marketing
- Python Feature Engineering Cookbook
- Artificial Intelligence By Example - Second Edition
- Hands-On Machine Learning on Google Cloud Platform
On-Demand Videos
- Exploratory Data Analysis with Pandas and Python 3.x
- Advanced Data Structures and Algorithms in Python
Instructor-Led Training
You'll be able to register for an Instructor-Led Training Session at any time after you've placed your order.
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16 aug
(1 dag)
9:00 - 4:30 BST Online (AnyWare) -
22 nov
(1 dag)
9:00 - 4:30 GMT Online (AnyWare) -
28 feb
(1 dag)
9:00 - 4:30 GMT Online (AnyWare) -
30 maj
(1 dag)
9:00 - 4:30 BST Online (AnyWare)
Important Python for Data Analytics FAQs
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What background do I need?
Just an interest in gaining foundational knowledge of data science. This data scientist training course is designed for technical and non-technical beginners.
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What on-demand content will I receive?
An outline of the content you will receive can be seen above. -
How will I access my course materials if I choose this method?
Once payment is received, you will receive an email from Learning Tree with all the links and information you need to get started. -
How can I sign up for a review session?
Once you are enrolled in the program, specific details and dates will be sent to you.
Har du frågor om vilken utbildning som är rätt för dig?
08-506 668 00
Why do we require your location?
It allows us to direct your request to the appropriate Customer Care team.
100 % nöjd. Eller få pengarna tillbaks!*
*Partner-delivered courses may have different terms that apply. Ask for details.