Tools for Data Science
This AI course delineates the Data Scientist's toolkit, instructs students in Python, R, and SQL, investigates RStudio and Jupyter notebooks, and discusses Git and GitHub for source code administration.
Description for Tools for Data Science
Features of Course
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by IBM
Duration: 18 hours (approximately)
Schedule: Flexible
Pricing for Tools for Data Science
Use Cases for Tools for Data Science
FAQs for Tools for Data Science
Reviews for Tools for Data Science
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Tools for Data Science
The AI tool is an open-source platform that simplifies AI agent development with features like Forge Template and Benchmarking Tool, enhancing accessibility for users of all technical levels.
The AI tool enables users to create interactive voice applications effortlessly through a visual interface, but may have limitations in complexity and customization compared to coding-based approaches.
The AI platform offers exceptional integration with OpenAI, personalized user dashboard, versatile SDKs, and a thriving marketplace for AI components, while also providing cloud-based accessibility and community support, with potential drawbacks including a learning curve and dependence on OpenAI API.
NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.
Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.
Plexo is an open-source project management tool with customizable features, integrated messaging, sophisticated reporting, and productivity optimization capabilities.
GPTBots offers AI-driven chatbot tools with robust NLP, seamless integration, customization options, and extensive analytics, enhancing user engagement and providing scalability, albeit with requirements for technical expertise and potential integration complexity.
Instill AI enhances AI application development with its no-code/low-code platform, versatile data pipeline, and pre-built components, offering accelerated development, adaptability, community support, while facing challenges like initial learning and platform dependence.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Superflows integrates an AI copilot into software products, offering in-app support via conversational messaging to streamline user interactions, enhance productivity, and improve overall user experience, albeit requiring thorough API documentation and initial setup investment.
Featured Tools
Develop a machine learning pipeline that utilizes Tidymodels to forecast hospital readmissions, with potential applications in healthcare analytics.
In brief, this course instructs students on the effective management of data biases, the prevention of overfitting, and the enhancement of model accuracy through the implementation of appropriate testing methods and feature engineering.
In a nutshell, this concentration helps business professionals get ready for the CDSP exam by teaching them how to put data science knowledge to use in real-world scenarios.
The subject matter addresses the Azure ML Python SDK for the development and administration of enterprise machine learning applications, as a component of the DP-100 certification program.
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.