Machine Learning Classes Near Me

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

Develop AI-powered web apps in this advanced Python course, where you'll use Flask and the OpenAI API to create dynamic sentiment analysis applications. Gain essential skills in web development, error handling, and deployment, taking your Python projects to a professional level with real-world AI integration.

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

Learn to apply machine learning algorithms in real-world scenarios using Python, with hands-on projects that cover regression, classification, and predictive modeling. Ideal for data professionals looking to advance their skills in a high-demand field.

The AI & Machine Learning Bootcamp at the University of San Diego, powered by Fullstack Academy, offers a dynamic 26-week part-time curriculum, welcoming students from various professional backgrounds into the world of artificial intelligence and machine learning. This program blends theoretical knowledge with practical application, using lectures, labs, and projects to equip students with the skills needed for existing roles or new careers in the data field.

The Online AI & Machine Learning Bootcamp at the University of North Florida, a 26-week part-time program powered by Fullstack Academy, offers students from diverse professional backgrounds the opportunity to master AI and machine learning skills. This comprehensive course combines lectures, labs, and projects, utilizing Fullstack Academy's active learning approach to provide practical, real-world tool application, preparing students for careers in the fast-growing data field.

The University of Oklahoma Outreach AI and Machine Learning Bootcamp is a 26-week, part-time program that combines theoretical and practical learning in AI, catering to individuals seeking to balance education with other commitments. This comprehensive curriculum, supported by Fullstack Academy’s active learning approach, empowers students to gain in-demand AI skills through lectures, labs, and projects, fostering both individual and collaborative learning experiences.

Transform your career with Louisiana State University's AI & Machine Learning Bootcamp, a part-time, 26-week program in partnership with Fullstack Academy. This comprehensive course is designed for individuals from diverse professional backgrounds, offering a deep dive into the practical and theoretical aspects of AI and machine learning. Through a blend of lectures, labs, and projects, you'll gain hands-on experience with real-world tools, preparing you to apply AI fundamentals in various roles or embark on a new journey in the burgeoning data field.

Embark on a career-transforming journey with the University of San Diego's AI & Machine Learning Bootcamp, a part-time, 26-week course created in association with Fullstack Academy. This program, ideal for individuals from diverse professional fields, offers an immersive online education in AI and machine learning principles. Engaging in lectures, labs, and practical projects, you'll develop the essential skills to implement AI solutions in the fast-expanding world of data technology.

Embark on a transformative journey with The University of Texas at Dallas's AI & Machine Learning Bootcamp, a program powered by Fullstack Academy. In 26 weeks, this part-time online course delves into the fundamentals of AI and machine learning, providing hands-on experience with the tools and technologies shaping the future of data and innovation.

Transform your career with the University of Michigan's AI & Machine Learning Bootcamp, an innovative program powered by Fullstack Academy. Over 26 weeks in a part-time, online format, this bootcamp guides students through the practical and theoretical aspects of AI and machine learning. Using real-world tools, students work on projects that apply AI fundamentals, setting them up for success in current roles or new careers in the rapidly growing field of data and AI technology.

Transform your career with Virginia Tech's AI & Machine Learning Bootcamp, an innovative program powered by Fullstack Academy. Over 26 weeks in this part-time, online course, students explore the practical and theoretical aspects of AI and machine learning, using real-world tools to prepare for roles in the rapidly growing data field.

This course in machine learning with R introduces novice R programmers a foundation in machine learning theory. The course covers the foundations of statistics and simple linear regressions, multiple linear regression and generalized linear models, kNN and Naïve Bayes, the curse of dimensionality, tree models, and SVMs. Students who complete this course will understand the mathematics behind machine learning algorithms and be able to use them in real-world situations.

This Python machine learning course teaches machine learning methods and modules with the Python code designed to implement them. The units of this course explain simple and complex linear regressions, classification methods for logistic regression, discriminant analysis, and naïve Bayes, support vector machines and tree-based methods, regularization strategies, and how to use clustering algorithms. Completion of this 20-week course will prepare students to use machine learning algorithms to analyze complex datasets and make logical predictions.