- Level Professional
- المدة
- الطبع بواسطة University of Colorado Boulder
-
Offered by
عن
In the Machine Learning specialization, we will cover Supervised Learning, Unsupervised Learning, and the basics of Deep Learning. You will apply ML algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Starting with supervised learning, we will cover linear and logistic regression, KNN, Decision trees, ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Then we turn our attention to unsupervised methods, including dimensionality reduction techniques (e.g., PCA), clustering, and recommender systems. We finish with an introduction to deep learning basics, including choosing model architectures, building/training neural networks with libraries like Keras, and hands-on examples of CNNs and RNNs. This specialization can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulderAuto Summary
Discover the "Machine Learning: Theory and Hands-on Practice with Python" course, curated for Data Science & AI enthusiasts. Led by expert instructors, this professional-level course delves into supervised and unsupervised learning, and introduces deep learning basics. Gain practical experience with real-world data using Python, Keras, and more. Ideal for recent graduates and professionals, this course is part of CU Boulder’s accredited programs on Coursera, offering flexible 8-week sessions and pay-as-you-go tuition. Perfect for those aiming to enhance their skills in machine learning.

Instructor
Geena Kim