Overview
This Python course is designed for those who want to learn how to work with data from the ground up with no prior coding experience. The course starts by covering the basics of Python programming before moving into more core data science skills like statistical analysis and regression modeling. From there, you will gain hands-on experience building classification models, tuning machine learning algorithms, and even training neural networks using Keras and TensorFlow.
During this Python training program, you will complete practical projects that mirror real-world data workflows, such as employee retention prediction, car pricing models, and image recognition using the MNIST dataset. These projects help reinforce skills and serve as portfolio pieces for job applications. The data science and machine learning training curriculum is structured to help you build confidence in using Python for data analysis and machine learning, even if you have no technical background.
During this Python training program, you will complete practical projects that mirror real-world data workflows, such as employee retention prediction, car pricing models, and image recognition using the MNIST dataset. These projects help reinforce skills and serve as portfolio pieces for job applications. The data science and machine learning training curriculum is structured to help you build confidence in using Python for data analysis and machine learning, even if you have no technical background.
- Course ID: GES3129
- Total Hours: 120
- Format: Asynchronous/Self-Paced
- Location: Online
- Schedule: 9 Months
- Credit(s) Earned: 12 CEU
- Instructor: Ed2go
- Cost: $2,700.00
- Category: Data Analytics
Hardware Requirements:
This course can be taken on either a PC or Mac. Chromebooks are not compatible.
Software Requirements:
PC: Windows 10 or later.
Mac: macOS 12 or later.
Browser: The latest version of Google Chrome or Mozilla Firefox is preferred. Microsoft Edge and Safari are also compatible.
Software must be installed and fully operational before the course begins.
Other:
Email capabilities and access to a personal email account.
Instructional Material Requirements:
The instructional materials required for this course are included in enrollment and will be available online.
What You Will Learn
Python fundamentals such as variables, data types, functions, loops, and control flow
Create and manipulate DataFrames using Pandas and perform exploratory data analysis (EDA)
Perform linear regression and evaluate models using a train-test split and residuals
Build and tune k-nearest neighbors models and explore feature scaling and distance metrics
Train ensemble models like random forests using scikit-learn and practice neural network design in TensorFlow
Submit predictions to real-world datasets using Kaggle workflows and build professional dashboards
Program Outcomes
Advanced your skill set with beginner-friendly Python and data science training, with no experience required
Review lessons focusing on practical skills that employers are looking for when hiring data and machine learning experts
Develop in-demand skills using tools such as Pandas, NumPy, Matplotlib, scikit-learn, and TensorFlow
