砺儒云课堂

The goal of this course is to help students to understand, explain, and apply the foundational mathematical concepts at the core of computer science and artificial intelligence.

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data, - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.

A computer network course covers fundamental principles, protocols, and technologies essential for designing, implementing, and managing networks. It introduces network architecture, protocols, and topologies, progressing to OSI and TCP/IP models. Students learn about network devices, including routers, switches, and firewalls, and explore data transmission mechanisms and encoding techniques. Wired and wireless networking technologies like Ethernet, Wi-Fi, and Bluetooth are examined, along with network security measures such as authentication and encryption. The course also addresses network management protocols like SNMP and troubleshooting techniques. Internet and web technologies, including HTTP, DNS, and IPv6, are covered, as well as emerging trends like SDN and IoT. Through hands-on labs and projects, students gain practical experience in configuring devices and analyzing network traffic. Real-world case studies provide insights into applying theoretical concepts. Overall, the course prepares students for careers in designing, securing, and managing computer networks effectively.