IBM Introduction to Machine Learning 专项课程
Learn Machine Learning through use cases. Get up to date with the theory of Machine Learning, and gain hands-on practice through projects on Machine Learning, one of the most relevant fields of modern AI.
Learners will complete projects designed to highlight analytical and Machine Learning skills. For each project, learners will produce a summary of their insights in a similar way as they would in a professional setting. This includes producing a final deliverable that would be presented to communicate insights to fellow Machine Learning practitioners, stakeholders, C-suite executives, and Chief Data Officers.
Learners are highly encouraged to compile their completed projects into an online portfolio that showcases the skills learned in this specialization.
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Can I just enroll in a single course?
Can I take the course for free?
此课程是 100% 在线学习吗？是否需要现场参加课程？
Ideally, you should have some background in Math, Stats, and computer programming, as most demonstrations, labs, and projects use Python programming language and concepts like matrix factorization, convergence, or stochastic gradient descent.This Specialization is designed specifically for scientists, software developers, and business analysts who want to round their analytical skills in Data Science, AI, and Machine Learning, but is also appropriate for anyone with a passion for data and basic Math, Statistics, and programming skills.
Do I need to take the courses in a specific order?
We recommend you to take the courses in the order presented in the specialization page, as each course builds on material presented in previous courses.
Will I earn university credit for completing the Specialization?
You will be able to use high-demand Machine Learning techniques in real world data sets. You will be able to derive and communicate insights from data using Exploratory Data Analysis, Supervised Learning, and Unsupervised Learning.