Programming for Everybody (Getting Started with Python)
This beginner's course covers the fundamentals of Python programming, including essential abilities such as functions, loops, and variable utilization.
Description for Programming for Everybody (Getting Started with Python)
Installation of Python and Initial Program: Acquire knowledge about installing Python and composing a preliminary program to obtain practical expertise in coding.
Fundamental Principles of Python: Comprehend the principles of Python programming, encompassing grammar, structure, and foundational language concepts.
Manipulating Variables: Master the utilization of variables for the storage, retrieval, and manipulation of data, a fundamental principle in programming.
Programming Tools, Functions and Iterations: Acquire proficiency in fundamental programming techniques, including functions for reusability and loops for iteration.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 24
Offered by: On Coursera provided by University of Michigan
Duration: 18 hours (approximately)
Schedule: Flexible
Pricing for Programming for Everybody (Getting Started with Python)
Use Cases for Programming for Everybody (Getting Started with Python)
FAQs for Programming for Everybody (Getting Started with Python)
Reviews for Programming for Everybody (Getting Started with Python)
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Programming for Everybody (Getting Started with Python)
Discover how to use Rust to apply DevOps ideas, automate system chores, and put logging and monitoring in place for effective application deployment and operation.
Gain an in-depth knowledge of fundamental concepts, including probability, vectors, calculus, and algebra, in order to establish a robust mathematical foundation for AI.
Gain an extensive understanding of the strategies for optimizing chatbot applications, integration with NLP/ML, and advanced ChatGPT prompting.
Acquire an in-depth knowledge of generative AI, its applications, and its models for the production of a variety of content.
Develop advanced AI techniques, including prompt engineering and chatbot development, as well as master large language models and their implementation on Google Cloud.
Through hyperparameter tuning, regularization, and TensorFlow application, this course emphasizes the optimization of machine learning models.
This course offers an introduction to the fundamentals of Python 3, encompassing control structures and basic data structures to assist learners in developing practical programming abilities.
This course provides practical experience with machine learning through case studies, concentrating on applying approaches across domains and laying the groundwork for deeper understanding of models and algorithms.
With an emphasis on CI/CD, cloud architecture, and training workflows, this course covers MLOps technologies and best practices for installing, assessing, and running ML systems on Google Cloud.
Using Vertex AI and BigQuery ML, the course instructs students on how to improve data quality, construct AutoML models, and optimize models using performance metrics.
Featured Tools
Explore the topic of AI-powered personalization by acquiring the skills necessary to utilize LangChain and ChatGPT.
To enhance machine learning models, this course offers fundamental understanding of artificial intelligence, machine learning methods like classification, regression, and clustering.
A practical guide to the use of generative AI for the purpose of composing, refining, and planning, utilizing structured and context-driven inputs.
Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.
A structured guide to the study of business opportunities in the chatbot space, as well as the comprehension, design, and deployment of chatbots using Watson Assistant.