Description for AI & ML for Business
Impact of AI on Industries: Discover how AI and ML are transforming business operations in finance, marketing, sales, and HR, thereby granting businesses a competitive advantage in the market.
Practical Applications for Business Leaders: Investigate the ways in which AI can be incorporated into organizational strategies to enhance business operations and stimulate innovation.
No Programming Necessary: This course is designed to provide actionable insights to non-technical business leaders without the necessity of coding expertise.
Case Studies and Real-World Context: Participate in practical case studies that assess comprehension and offer real-world applications of AI concepts in business environments.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 10
Offered by: On Udemy provided by Analytics Vidhya
Duration: 5h 42m
Schedule: Full lifetime access
Pricing for AI & ML for Business
Use Cases for AI & ML for Business
FAQs for AI & ML for Business
Reviews for AI & ML for Business
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for AI & ML for Business
Marbleflows is a no-code funnel builder powered by AI for entrepreneurs and businesses, offering distinctive features and accessibility for easy funnel construction and lead conversion optimization.
The AI tool provides a comprehensive solution for managing AI vision intelligence, offering sophisticated computer vision systems, complete automation in horticulture robotics, and user administration features for seamless operation and control.
NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.
Coginiti's AI-Assisted SQL Development boosts SQL development efficiency with instant query assistance and optimization, alongside on-demand learning resources, while facing integration restrictions and an initial learning curve.
Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.
Accubits provides tailored blockchain and AI solutions, offering expert technology consulting and enterprise solutions, recognized for industry leadership and innovation, catering to a diverse clientele but potentially overwhelming for small-scale enterprises.
The platform offers innovative gamified assessments, AI-audited algorithms, and digital interviewing for unbiased candidate evaluation, enhancing hiring efficiency and reducing bias, while providing deep talent insights and aligning talent development with business objectives.
Abacus.ai offers end-to-end MLOps capabilities and advanced AI methodologies, including neural networks, to provide precise models for enterprise data analysis needs, along with comprehensive monitoring and real-time machine learning features.
Nuclia is a cloud-based platform that creates AI-powered search engines, utilizing sophisticated algorithms for efficient data retrieval and offering features like NLP, automated data enrichment, and custom analytics.
Aigur is an AI platform that simplifies data pipeline management and the creation of AI-based applications, offering features such as plan management, backend logic design, UI components, and a user-friendly API, all with a substantial free plan.
Featured Tools
Develop a machine learning model using PySpark to forecast customer attrition and acquire practical experience in AI-driven business solutions.
By utilizing modern Python libraries, investigating machine learning tools, and delving into logistic regression, decision trees, and linearly inseparable data, you can master AI with our course.
Learn to use TensorFlow for computer vision and natural language processing, manage image data, prevent overfitting, and train RNNs, GRUs, and LSTMs on text repositories.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
Machine learning mathematics. Find out about the mathematical prerequisites for applications in machine learning and data science.