Introduction and Overview
Certified Deep Learning Specialist – CDLS
Many international firms are engaged in the development of technologies categorized under the field of Artificial Intelligence. The systems equipped with Artificial Intelligence do not require constant human intervention to carry out the designated process. Such an intelligent computing system has the ability to learn things on its own according to the situation.
Technologies such as deep learning, intelligent robots and neuro-linguistic programming under Artificial Intelligence have been aiding in the enhancement of the existing computing systems to produce high-value prediction.
The global artificial intelligence market is expected to reach USD 35,870.0 million by 2025 from its direct revenue sources, growing at a CAGR of 57.2% from 2017 to 2025. And the Deep Learning market, in particular, is expected to be worth USD 1772.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022.
The Asia Pacific regional market is expected to be the fastest-growing market for Deep Learning, owing to the improvements in information storage capacity, high computing power, and parallel processing. The major drivers for the growth of the Deep Learning market are various industry verticals such as advertisement, finance and automotive.
This course will focus on the implementation of one of the newest libraries for implementing Deep Learning, called the Tensor Flow. The certification leverages intuitive approach to build complex models with humans like intelligence that will help to solve real-world problems using Machine Learning and Deep Learning techniques.
After the course, participants will have a good understanding to build intelligent computing models in Python Jupiter Notebook platform using Scikit Learn and Tensor Flow. Participants will appreciate that Deep Learning is showing promise in areas where the traditional Artificial Intelligence approaches have failed in the past.
- Cloud Operations Engineer
- Senior Cloud Operations Engineer
- Data Analyst – Statistics and Mining
- Data Analyst – Text Analytics
- Operations Research Analyst
- Understand the overview of Machine Learning techniques
- Understand the different model selection methods in Machine Learning
- Understand the basic types of Deep Neural Networks (MLP, CNN, RNN, LSTM)
- Design and build Machine Learning models in Python Jupyter notebooks using Scikit Learn framework
- Design and build an end to end model using Tensor Flow in Python Jupyter notebooks
Participants are preferred to have experience in software development, business domain or data/business analysis.
- Machine Learning Categories
- Supervised Learning Algorithms
- Unsupervised Learning Algorithms
- Reinforcement Learning
- Machine Learning Challenges
As part of the written examination, each participant will be assessed individually on the last day of the training for their understanding of the subject matter and ability to evaluate, choose and apply them in specific context and also the ability to identify and manage risks. The assessment focuses on higher levels of learning in Bloom’s taxonomy: Application, Analysis, Synthesis and Evaluation.
This written examination will primarily consist of 40 multiple choice questions spanning various aspects as covered in the program. It is an individual, competency-based assessment.
- Upon passing the course, you will be awarded,
“Certified Deep Learning Specialist( CDLS )”
- Certification Body :