Introduction
This program will help student learn Python for data science, as well as programming in general. This beginner-friendly Python course will take them from zero to programming in Python in a matter of hours. Also, they will learn how to perform data analytics with Python via lectures and hand-on labs. Some real-life cases will be shared in the course. Moreover, students will have chances to understand how machine learning models can be built on AWS platform. These can raise their interests about ML and encourage them to pursue their careers in this area.
Course Outline:
Module I: Python Programming, 9 hours
- Python Basics
- Control Flow
- Python Array, List and Tuple
- Python Dictionary
- Python Functions
- Errors and Exception Handling
- Files handling
- NumPy Basic
- Pandas Basic
- Data Collection and Processing with Python
- Python Objects and Classes
- Working with Data in Python
Module II: Data Analytics with Python, 6 hours
- Concepts of Data Analytics
- Importing Datasets
- Cleaning the Data
- Data Frame Manipulation
- Summarizing the Data
- Building Machine Learning Regression Models
- Building Data Pipelines
Module III: Building a ML Model on Cloud, 3 hours
- K-Means Algorithm
- Machine Learning Life-cycle: Develop, Build and Deploy
- Building ML models with Amazon SageMaker (Amazon Web Services)
Module IV: Labs on AWS Cloud, 6 hours
- Lab 1 – Extract Structured Data with Amazon Textract
- Lab 2 – Analyze insights in text with Amazon Comprehend
- Lab 3 – Add Voice to Your WordPress Site
- Lab 4 – Deploy a machine learning model with Sagemaker
- Lab 5 – Perform Sentiment Analysis on AWS
- Lab 6 – Create and query an index with Amazon Kendra
Our assessment on this training: