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Introduction to Python for Data Analytics
Level: Foundation
Rating:
4.41/5 Based on 51 Reviews
Gain the skills you need to analyze and visualize 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 analyzing data to answer key business questions.
Key Features of this Python for Data Analytics Training:
- Attend online or bring this course to your facility
- After-course instructor coaching
You Will Learn How To:
- Use Python for statistical data analysis
- Generate summary statistics with pandas
- Clean, transform, and reshape data
- Glean insights from the data through visualization
Choose the Training Solution That Best Fits Your Individual Needs or Organizational Goals
TRAINING AT YOUR SITE
Team Training
- Bring this or any training to your organization
- Full - scale program development
- Delivered when, where, and how you want it
- Blended learning models
- Tailored content
- Expert team coaching
Customize Your Team Training Experience
CONTACT USBLENDED LEARNING
On-Demand & Live Review Session
Unlimited annual access to:
- 12 eBooks
- 2 on-demand video courses
- 1-day instructor-led training course
Standard $1740/Year CAD
Government $1530/Year CAD
ADD TO CARTPRODUCT #70I7
Save More On Training with FlexVouchers – A Unique Training Savings Account
Our FlexVouchers help you lock in your training budgets without having to commit to a traditional 1 voucher = 1 course classroom-only attendance. FlexVouchers expand your purchasing power to modern blended solutions and services that are completely customizable. For details, please call 888-843-8733 or chat live.
Team Training
On-Demand & Live Review Session
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
One Day Instructor-Led Review
You'll be able to register for a Training Review Session at any time after you've placed your order.
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May 11
(1 Day)
9:00 AM - 4:30 PM EDT Online (AnyWare) -
Aug 17
(1 Day)
9:00 AM - 4:30 PM EDT Online (AnyWare) -
Nov 16
(1 Day)
9:00 AM - 4:30 PM EST Online (AnyWare) -
Jan 31
(1 Day)
9:00 AM - 4:30 PM EST Online (AnyWare) -
May 9
(1 Day)
9:00 AM - 4:30 PM EDT 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.
Questions about which training is right for you?
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It allows us to direct your request to the appropriate Customer Care team.
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