Practical Data Science with MATLAB Specialization
The goal of this course is to provide professionals with the necessary data science abilities in MATLAB so that they can carry out practical activities in businesses that rely heavily on data without having to learn extensive programming.
Description for Practical Data Science with MATLAB Specialization
-
Industry-Relevant Skills: Directs on sought-after skills in data visualization, analysis, and modeling, essential to sectors such as healthcare, automotive, and technology.
-
MATLAB for Data Science: MATLAB, a favored tool in engineering and research, with complimentary access granted throughout the specialization.
-
Prerequisites: Requires subject expertise and a fundamental comprehension of statistics, encompassing topics such as histograms, means, and curve fitting.
-
Efficient Learning Path: Provides an expedited approach to acquiring proficiency in practical data science activities without requiring much programming or statistical expertise.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by MathWorks
Duration: 2 months at 4 hours a week (approximately)
Schedule: Project-based
Pricing for Practical Data Science with MATLAB Specialization
Use Cases for Practical Data Science with MATLAB Specialization
FAQs for Practical Data Science with MATLAB Specialization
Reviews for Practical Data Science with MATLAB Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Practical Data Science with MATLAB Specialization
The AI tool specializes in sentiment analysis, competitive analysis, custom analytics, Amazon marketplace analysis, review export, comprehensive help resources, and social media presence to meet diverse user needs effectively.
The AI tool enables organizations to create personalized multi-channel experiences for their clientele, featuring audience segmentation and a user-friendly platform with a complimentary 14-day trial and enterprise pricing options.
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
The AI generator, drawing from various sources, facilitates user interaction to produce content, making it beneficial for startups and individuals seeking to explore and enhance their knowledge across different subjects.
The AI tool utilizes advanced technology to streamline product research and feedback analysis, offering quick insights, collaborative opportunities, integration options, a user-friendly interface, a free tier option, and team collaboration features.
CensusGPT is an AI tool that simplifies access to census data, offering tabular data and visual representations in response to user queries. It targets economists, researchers, and individuals interested in demographic analysis, leveraging the TextSQL framework for seamless interaction with datasets.
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.
Breadcrumb.ai swiftly converts data into interactive presentations, reports, and interfaces, leveraging AI for intuitive insights exploration and seamless integration with various data sources, facilitating quick decision-making.
Hostcomm CXCortex offers AI-powered quality assurance and CX analytics solutions, leveraging data-driven segmentation and real-time insights to enhance consumer experiences and drive revenue growth for enterprises.
Featured Tools
Learn to integrate sophisticated tools such as ChatGPT into cybersecurity practices while managing AI and machine learning risks.
Gain practical skills in relational and NoSQL databases, Big Data tools, and data pipelines for comprehensive data engineering tasks.
Gain essential skills in Probability Theory for managing uncertainty, structured into five modules with practical exercises, covering topics like Probability, Conditional Probability, and offering an engaging online learning experience.
The course outlines the learning objectives for understanding XGBoost algorithm theory, performing exploratory data analysis, and implementing XGBoost classifier models using Scikit-Learn.
Learn to write efficient queries, perform correlations, create visualizations, and leverage sub-searches and lookups to become a Search Expert.