10 Courses and Certifications

IBM Machine Learning Courses & Certifications

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Unsupervised Machine Learning

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Certificate

Unsupervised Machine Learning

7 Weeks
Intermediate
3,277
Supervised Machine Learning Regression

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Certificate

Supervised Machine Learning: Regression

6 Weeks
Intermediate
3,277
Introduction to Deep Learning and Neural Networks with Keras

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Certificate

Introduction to Deep Learning & Neural Networks with Keras

In the present times where the advances in technology have shifted to IoT (Internet of Things), the concept of Deep Learning can be foreseen as one of the crucial ones, to be understood and well researched. Deep learning is faster and easier to develop and deploy as well. The Introduction to Deep Learning & Neural Networks with Keras certification course, the participants will get a deep insight into the Deep learning models. Furthermore, they will also be able to create models of Deep learning by making use of the Keras library.

The entrant will be introduced to exhilarating applications of Deep Learning. They will be learning about various deep learning algorithms and neural networks which are inspired by the functioning of neurons and the brain with respect to data processing. They will also get an insight into the working of the neural networks to feed the data throughout the network.

The Introduction to Deep Learning & Neural Networks with Keras training will provide knowledge about optimisation of variables as per the defined function, gradient descent algorithm, backpropagation, and updating the weights and biases of neural networks. Furthermore, the entrant will be taught about the activation functions and vanishing gradient problems. 

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5 Weeks
Intermediate
3,369
Skills Covered:
Machine learning Knowledge of Artificial Intelligence Knowledge of deep learning
PyTorch Basics for Machine Learning

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IBM via Edx
Certificate

PyTorch Basics for Machine Learning

The PyTorch Basics for Machine Learning certification programme is offered by IBM to arm you with the skills for implementing classic machine learning algorithms. You will get to know how PyTorch is used to optimise and create deep learning models. 

During the PyTorch Basics for Machine Learning training, you will learn important models such as linear and logistic regression models. This introductory-level programme will teach you how to train your models and their related concepts like gradient descent, cost and loss.

With the learnings of edX’s PyTorch Basics for Machine Learning course, you will learn to save your training and model in apps like checkpoints, early stopping and cross-validation for hyperparameter selection. Also, basics around the linear object, like their interaction with data with a distinctive number of samples and different dimensions, will be cleared.

The PyTorch Basics for Machine Learning course also includes a final project in the end to assess your skills and performance. You can even get a paid instructor-signed certification after completing the course. The learners also can audit the self-paced programme without paying the fee for a limited duration. 

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5 Weeks
Beginner
Skills Covered:
Machine learning Knowledge of deep learning Knowledge of Numpy
Deep Neural Networks with PyTorch

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Certificate

Deep Neural Networks with PyTorch

The Deep Neural Networks with PyTorch certification course will teach candidates, how to use Pytorch to create deep learning models. It is a part of the IBM AI Engineering Professional Certificate. There are a total of 6 courses in that specialisation. The Deep Neural Networks with PyTorch training course is the fourth one of them. Artificial intelligence or AI is revolutionising whole industries by transforming the way businesses exploit knowledge to make decisions across sectors. Organisations need skilled AI engineers who use cutting-edge approaches such as machine learning algorithms and deep learning neural networks to provide their companies with data-driven actionable intelligence in order to remain competitive. This Technical Certificate of 6 courses is designed to equip candidates with the tools which are needed to excel as an Artificial Intelligence or Machine Learning engineer in their career. 

Using programming languages such as Python, candidates will master the basic principles of machine learning and deep learning, which includes supervised and unsupervised learning. Candidates will also obtain a digital badge from IBM acknowledging their proficiency in AI engineering in addition to receiving a Technical Certificate from Coursera.

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4 Weeks
Intermediate
4,085
Skills Covered:
Knowledge of deep learning
Advanced Machine Learning and Signal Processing

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Certificate

Advanced Machine Learning and Signal Processing

The online program on Advanced Machine Learning and Signal Processing by Coursera is a part of the series of programs that are offered in the domain of “advanced machine learning and signal processing”. The Advanced Machine Learning and Signal Processing training is part of the courses that are offered by IBM on advanced data science specialization. In the course, the frameworks for python using SparkML and Scikit-Learn will be introduced. The Advanced Machine Learning and Signal Processing certification syllabus will be covered on the digital platform within a time frame of 28 hours.

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4 Weeks
Expert
4,018
Skills Covered:
Machine learning
Machine Learning Rapid Prototyping with IBM Watson Studio

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Certificate

Machine Learning Rapid Prototyping with IBM Watson Studio

The Machine Learning Rapid Prototyping with IBM Watson Studio certification course will be allowing the students to work in the emerging technologies of AI. The syllabus is included in the online course Machine Learning Rapid Prototyping with IBM Watson Studio by Coursera. The online programme is  100% online programme and the course is having a duration of eight hours. The Machine Learning Rapid Prototyping with IBM Watson Studio certification syllabus includes the chapters of- Classification Prep Demo, Regression Prep Demo, Multi-armed Bandit Approach, Demo Classification: Making Changes to the Models, Automated Data Preparation, DAUB Algorithm, The model selection problem and others.

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3 Weeks
Intermediate
Skills Covered:
Machine learning
Machine Learning Introduction for Everyone

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Certificate

Machine Learning Introduction for Everyone

3 Weeks
Beginner
Free
Data Engineering and Machine Learning using Spark

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Certificate

Data Engineering and Machine Learning using Spark

3 Weeks
Beginner
Free
Supervised Machine Learning Classification

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Certificate

Supervised Machine Learning: Classification

A part of the multiple series programme, the online session on Supervised Machine Learning: Classification by Coursera provides the students with a detailed emphasis on the main types of modelling that are involved with the genre of machine learning. The students will learn elaborately to train the predictive models that are involved and used across various domains. The Supervised Machine Learning: Classification certification syllabus will be covered on the online platform by the students over a time frame of 24 hours. The course will train the students professionally in the domain of machine learning.

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Intermediate
3,384
Skills Covered:
Machine learning

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