Coursera
Paid Course
English
Certificate Available
35 weeks long, 3 hours a week
Overview
Class Central Tips
Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML engineer. You’ll master fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning, using programming languages like Python. You’ll apply popular machine learning and deep learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow to industry problems involving object recognition, computer vision, image and video processing, text analytics, natural language processing (NLP), recommender systems, and other types of classifiers. Through hands-on projects, you’ll gain essential data science skills scaling machine learning algorithms on big data using Apache Spark. You’ll build, train, and deploy different types of deep architectures, including convolutional neural networks, recurrent networks, and autoencoders. In addition to earning a Professional Certificate from Coursera, you will also receive a digital badge from IBM recognizing your proficiency in AI engineering.
Syllabus
Course 1: Machine Learning with Python
- Offered by IBM. This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. ... Enroll for free.
Course 2: Introduction to Deep Learning & Neural Networks with Keras
- Offered by IBM. Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning ... Enroll for free.
Course 3: Introduction to Computer Vision and Image Processing
- Offered by IBM. Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such ... Enroll for free.
Course 4: Deep Neural Networks with PyTorch
- Offered by IBM. The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors ... Enroll for free.
Course 5: Building Deep Learning Models with TensorFlow
- Offered by IBM. The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant ... Enroll for free.
Course 6: AI Capstone Project with Deep Learning
- Offered by IBM. In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use ... Enroll for free.
- Offered by IBM. This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. ... Enroll for free.
Course 2: Introduction to Deep Learning & Neural Networks with Keras
- Offered by IBM. Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning ... Enroll for free.
Course 3: Introduction to Computer Vision and Image Processing
- Offered by IBM. Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such ... Enroll for free.
Course 4: Deep Neural Networks with PyTorch
- Offered by IBM. The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors ... Enroll for free.
Course 5: Building Deep Learning Models with TensorFlow
- Offered by IBM. The majority of data in the world is unlabeled and unstructured. Shallow neural networks cannot easily capture relevant ... Enroll for free.
Course 6: AI Capstone Project with Deep Learning
- Offered by IBM. In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use ... Enroll for free.
Taught by
Alex Aklson, Joseph Santarcangelo, Romeo Kienzler and SAEED AGHABOZORGI
