Description for Introduction to Data Science in Python
Features of Course
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by University of Michigan
Duration: 34 hours (approximately)
Schedule: Flexible
Pricing for Introduction to Data Science in Python
Use Cases for Introduction to Data Science in Python
FAQs for Introduction to Data Science in Python
Reviews for Introduction to Data Science in Python
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Introduction to Data Science in Python
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Welcome to the 'Gen AI for Code Generation for Python' course, where you will begin a journey to hone and expand your abilities in the field of code generation using Generative AI.
Learn to use the latest LLM APIs, the LangChain Expression Language (LCEL), and develop a conversational agent.
Master coding basics and create a Hangman game using generative AI tools like Google Bard in a beginner-friendly, 1.5-hour guided project.
Learn about AI principles and platforms like IBM Watson and Hugging Face, integrate RAG technology for chatbot intelligence, create web apps using Python libraries, and develop interfaces with generative AI models and Python frameworks.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Master Python programming for software development and data science, including core logic, Jupyter Notebooks, libraries like NumPy and Pandas, and web data gathering with Beautiful Soup and APIs.
Acquire practical skills in fundamental machine learning models and their applications using PyTorch, as utilized by leading tech companies.
Featured Tools
Besides Python programming and data science fundamentals, the course covers supervised machine learning regression, which includes training models for continuous outcomes, error metrics, Elastic Net, LASSO, Ridge regularization, and data science fundamentals for aspiring data scientists.
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.
By learning how to analyze health data and sequence genomes using AI, this course equips students with the tools they need to contribute to medical research.
This course equips students with the necessary business leadership skills and technical knowledge to propel the success of ML.
Develop Your Own Internet of Things (IoT) Device. In a mere six courses, develop and construct a basic IoT device.