custom code
gtranslate code
Menu
Menu
Automating Administration with PowerShell
Microsoft Office Excel Level 1
Microsoft Office Excel Level 2
Microsoft Office Excel Level 3
Data List Management
Microsoft Office Excel Level 4
Spreadsheet Analysis
Microsoft Office Excel Level 5 VBA Macros
Microsoft SharePoint Course for End Users
Microsoft Office Powerpoint Level 1
Microsoft Office Powerpoint Level 2
Microsoft Office Outlook Level 1
Microsoft Office Outlook Level 2
AI Engineer Level 2: Data Science with Python
Course Outlines
- Data Science and Data Analytics Overview
- Statistical Analysis and Business Applications
- Python Environment Setup
- Mathematical Computing with Python (NumPy)
- Scientific computing with Python (Scipy)
- Data Manipulation with Pandas
- Machine Learning with Scikit–Learn
- Natural Language Processing with Scikit Learn
- Data Visualization in Python using matplotlib
- Web Scraping with BeautifulSoup
- Python integration with Hadoop MapReduce and Spark
What you'll learn
- Understanding of Data Science processes, data processing, data exploration, data visualizationa and hypothesis building.
- The basics of statistics, creating python environment and other tools and libraries.
- Perform high-level mathematical computing using the NumPy library.
- Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO.
- Perform data analysis and manipulation using Pandas library.
- In depth understanding of Machine Learning using the Scikit-Learn package.
- In-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, K-NN and dimensionality reduction
Course Content
- Understanding of Data Science processes, data processing, data exploration, data visualizationa and hypothesis building.
- The basics of statistics, creating python environment and other tools and libraries.
- Perform high-level mathematical computing using the NumPy library.
- Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO.
- Perform data analysis and manipulation using Pandas library.
- In depth understanding of Machine Learning using the Scikit-Learn package.
- In-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, K-NN and dimensionality reduction
Customize a Course
We will be happy to assist you for inquiries about a customized scheduled or program:
Rachael McPherson, Director of Sales
☎(250)882-9549 📧[email protected]
Caroline Santos, Corporate and Custom Sales Manager- Eastern Canada
☎(514)771-3206 📧[email protected]
Course Info
Prerequisites
AI Engineer Master Level 1: Introduction to Artificial Intelligence
Duration
20 Hours
You may also like
popup and lms tutor hidden code
X
Customize A Course
We will be happy to assist you for inquiries about a customized scheduled or program:
