Machine Learning Engineer Certification
There are many Machine Learning opportunities on the internet, including many certifications and courses. This article discusses the best Machine Learning certifications available to engineers. Many of these certifications are accessible for free, while others require payment.
1. Stanford University Machine Learning Certification
Stanford University provides this qualification via Coursera, which Andrew Ng taught, who is well-known and highly esteemed. It addresses both theoretical and functional aspects of Machine Learning subjects since both are important for Machine Learning engineers to be effective in their profession. This course allows students to practice problem-solving skills by posing questions they might face in the real world. Linear Regression, Linear Algebra, Octave/MATLAB, Logistic Regression, Regularization, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction, Anomaly Identification, and Recommender Systems are only some of the subjects discussed in this certification.
2. TensorFlow Developer Professional Certificate
Deeplearning.ai’s TensorFlow Developer Professional Certificate, available through Coursera, allows students to study TensorFlow and its neural network and machine vision software. You’ll even understand how to interpret natural language (NLP). There’s also an emphasis on real-world problem solving, with a perspective on image data and avoiding overfitting. RNNs, GRUs, and LSTMs are some of the main algorithms explored.
This certificate is divided into four sections:
- Applications of TensorFlow in Artificial Intelligence and Deep Learning
- How TensorFlow uses Convolutional Neural Networks
- Sequences, Time Series, and Prediction
- Natural Language Processing in TensorFlow
3. Getting Started with AWS Machine Learning
This course and certificate are offered through Coursera by AWS. It is an excellent way to focus on learning Machine Learning for AWS and its applications. This short course covers Machine Learning, Computer Vision, and Amazon Sage Maker.
This course would help you learn to build intelligent applications using Amazon AI services like Amazon Comprehend, Amazon Rekognition, Amazon Translate, etc. It will enable you to create, train and deploy a model using Amazon SageMaker with built-in algorithms and Jupyter. It also covers AWS DeepLens, the world's first deep learning-enabled video camera for developers.
4. Augmented Data Visualization with Machine Learning
This course is available via Udemy. This course intends to show you how to create modern data visualization applications through a series of exercises. Via hands-on experience for Oracle Analytics, you can focus on machine learning frameworks for predictive analytics and advanced data flow functionality. Every segment is jam-packed with video and screencasts that illustrate each analytics function.
The study will cover data processing and visualization, building and visualizing machine learning models, classification, correlation and regression, and data aggregation. It also provides insight into big data, data flow, SaaS applications, and business intelligence, among others.
5. Building Recommender Systems with Machine Learning and AI
LinkedIn provides this certification. This study concentrates on recommender programs that incorporate machine learning and artificial intelligence. Via this qualification, you will be able to work with automatic recommendation systems. You’ll be able to make your own, like neighborhood-based collaborative filtering, among other items. This course not only covers real-world Machine Learning implementations it also contains case studies.
The instructor Frank Kane is recognized as a pioneer in the sector. He worked at Amazon for over nine years, where he was in charge of all of the company's customized product recommendation techniques. He tells you how to build your recommender schemes. You will get your feet wet by creating your platform for testing algorithms and creating neural networks with Amazon DSSTNE, AWS SageMaker, and TensorFlow.
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