Applied Data Science with Python Specialization
Learn to perform inferential statistical analysis, assess and improve data visualizations, integrate machine learning into data analysis, and analyze social network connectivity.
Description for Applied Data Science with Python Specialization
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by University of Michigan
Duration: 4 months at 10 hours a week
Schedule: Flexible
Pricing for Applied Data Science with Python Specialization
Use Cases for Applied Data Science with Python Specialization
FAQs for Applied Data Science with Python Specialization
Reviews for Applied Data Science 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 Applied Data Science with Python Specialization
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
Become an ethical AI practitioner by developing the ability to identify and resolve ethical challenges in AI and data science initiatives.
Gain practical skills and foundational knowledge of generative AI, along with insights from AWS AI practitioners on how companies leverage cutting-edge technology for value generation.
Learn how to use Gemini for Google Workspace to boost productivity and efficiency in Gmail through its generative AI features.
Gain comprehensive understanding of generative AI principles, apply them to code generation, develop expertise in GANs and autoencoders, and achieve practical proficiency.
The course outlines the learning objectives for understanding XGBoost algorithm theory, performing exploratory data analysis, and implementing XGBoost classifier models using Scikit-Learn.
Compare & Review AI Tool Directory AI Course Marketplace
AI Tool Categories
AI Productivity ToolsAI Image GeneratorsAI Text GeneratorsAI Video GeneratorsAI Audio GeneratorsAI Art GeneratorsMisc AI ToolsAI Code GeneratorsFree AI ToolsAI Functions
Marketing AI ToolsAI Tools for EducationAI Tools for ResearchAI Tools for FinanceAI Project Management ToolsLegal AI ToolsAI Tools for E-commerceAI Agents For AutomationAI Tools for BusinessAI Tools for Real EstateAI Course Categories
AI & Machine Learning CoursesGenerative AI CoursesData Science CoursesComputer Science CoursesAI Courses for BeginnersContact Us: [email protected]
Aimed Labs