IBM AI Engineering 专业证书
Launch Your Career in AI Engineering
By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Machine Learning and Deep Learning, and become armed with skills for a career as an AI Engineer. You will also complete a Capstone Project and demonstrate ability to present and communicate outcomes of deep learning projects
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来自IBM AI ENGINEERING的热门评论
One of the best & most interesting courses in this complete data science specialization. As a naive to this domain, I aquired a ton of insights in Machine Learning.
This was my favorite IBM specialization course, well explained and very interesting.\n\nThis course has inspired me to study Machine Learning more deeply.
Best course till now in the entire specialization.
The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.
could be split in two courses to be given enough focus. it was very condensed and needed more time and explanation in each section. The instructor was very good but more details would have been nice
The instructor was awesome. His voice was crisp and to the point. The course is actually well laid out with proper structure. Altogether a great learning experience. Cheers... Keep up the good work.
This is a very good start for Machine leaning with Python. I didnt have much idea about ML concepts but this course gave me great understanding on each topic and lot of learning. Awesome Course !!
This was a very informative course. The videos provided a good background on the concepts and I found the labs especially helpful for learning to implement Python code for each technique covered.
此课程是 100% 在线学习吗？是否需要现场参加课程？
This Professional Certificate consists of 6 self-paced courses. Effort required to complete each course is 4-5 weeks if spending 2-4 hours per week. At this rate the entire specialization can be completed in 3-6 months.
What background knowledge is necessary?
Do I need to take the courses in a specific order?
It is highly recommended to complete the courses in the suggested order.
At this time there is no university credit for completing courses in this specialization.
What will I be able to do upon completing the Specialization?
Upon completing this Professional Certificate you will be able to:
- Describe what is Machine Learning (ML), Deep Learning (DL) & Neural Networks
- Explain ML algorithms including Classification, Regression, Clustering, and Dimensional Reduction
- Implement Supervised and Unsupervised ML models using scipy and scikitlearn
- Express how Apache Spark works and how to perform Machine Learning on Big Data
- Deploy ML Algorithms and Pipelines on Apache Spark
- Demonstrate an understanding of Deep Learning models such as autoencoders, restricted Boltzmann machines, convolutional networks, recursive neural networks, and recurrent networks
- Build deep learning models and neural networks using the Keras library
- Utilize the PyTorch library for Deep Learning applications and build Deep Neural Networks
- Explain foundational TensorFlow concepts like main functions, operations & execution pipelines
- Apply deep learning using TensorFlow and perform backpropagation to tune the weights and biases
- Determine what kind of deep learning method to use in which situation and build a deep learning model to solve a real problem
- Demonstrate ability to present and communicate outcomes of deep learning projects