Description for Statistics with Python Specialization
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by University of Michigan
Duration: 1 month at 10 hours a week
Schedule: Flexible
Pricing for Statistics with Python Specialization
Use Cases for Statistics with Python Specialization
FAQs for Statistics with Python Specialization
Reviews for Statistics with Python Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Statistics with Python Specialization
AI-Signals, driven by AI algorithms, offers precise trading insights including institutional concepts, automated analysis, and access to a VIP Discord community, while potential intermittent errors and subscription requirements may be considerations.
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.
Featured Tools
Integrate AI-assisted code into a Python project, optimize and debug with AI, and create detailed documentation using ChatGPT.
Learn to use AutoML with Python and H2O AutoML to solve business analytics problems.
Develop generative AI capabilities for data analytics. Learn about generative AI to advance your career as a data analyst! No prior experience is required.
Understand Python methodologies like lambdas, csv file manipulation, and prevalent data science features, including cleansing and processing DataFrame structures.
Learn how to leverage GenAI's capabilities and manage its risks to enhance decision-making, productivity, and customer value in organizations.