Description for ML and AI with Python
Advanced Data Science Techniques: Study machine learning models, random forests, and decision trees by examining sample data sets.
Model Training and Prediction: Acquire the knowledge necessary to train machine learning models to anticipate solutions to intricate problems.
Resolving Model Issues and Data Bias: Comprehend the process of identifying data bias and preventing problems such as underfitting and overfitting.
Machine learning libraries in Python: Establish a strong foundation for the use of Python libraries in AI and machine learning, in anticipation of future research.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On edX provided by HarvardX
Duration: 4�5 hours per week approx 6 weeks
Schedule: Flexible
Pricing for ML and AI with Python
Use Cases for ML and AI with Python
FAQs for ML and AI with Python
Reviews for ML and AI with Python
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML and AI with Python
Browse AI is an advanced tool for automating data extraction and monitoring from websites, empowering users with no-coding solutions and intuitive features for efficient data management.
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.
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.
MOSTLY AI's Synthetic Data Platform offers a robust solution for generating privacy-safe synthetic datasets that preserve the structure and statistical characteristics of authentic data, enhancing adaptability and versatility for various applications.
Julius AI is a user-friendly data analysis tool with advanced capabilities for structured and unstructured data, offering data visualizations, automation, and data export options, backed by stringent data privacy measures, making it suitable for both novice and experienced users.
Sprig is an AI-driven user insights application that facilitates gathering and analyzing user data through in-product studies, surveys, and recordings, empowering teams to enhance product experiences and drive superior results with AI-generated insights.
CustomerIQ is an AI-driven platform that aggregates and analyzes consumer feedback from various channels, enabling organizations to prioritize tasks, align around customer needs, and develop solutions with confidence, all through a user-friendly interface.
Ray, an AI-powered application, simplifies the process of creating and analyzing surveys and forms, offering integration capabilities, bias detection features, and insightful analysis tools to streamline data collection and decision-making.
Appinion, an AI-driven sentiment analysis tool, leverages deep learning models and topic modeling to provide accurate insights from user feedback, aiding organizations in making informed decisions and enhancing app store applications.
Featured Tools
Join us on a transformative voyage with our Generative AI for NLP Specialization, which is specifically designed to enhance your comprehension of AI-driven language models, from the fundamental concepts to the most advanced applications. While investigating the architecture and applications of large language models, enhance your proficiency in Python programming, machine learning, NLP, and Generative AI techniques.
Learn the fundamentals of artificial intelligence (AI) and machine learning. Formulate a deployment strategy that capitalizes on the most advanced technologies to integrate AI, ML, and Big Data into your organization.
Understand Generative AI, its potential and challenges, and the responsible use of the Gemini Enterprise add-on.
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
This program provides a pragmatic introduction to machine learning and data mining using R, encompassing fundamental techniques and tackling significant data analysis difficulties.