Deep Learning Courses & Certifications Online
Deep learning is all set to mark it digital impact across different domains and the job prospects are bright. As per a research by MarketsandMarkets, Artificial Intelligence, Machine Learning, and deep learning market is expected to grow to USD 11.4 billion by 2023.
For most of computing history, computers have been programmed with a set of coded rules to compute and make decisions. The progress powered by improvement in abstractions, hardware, and frameworks. That changes with Deep learning where computers can “learn” from the input data. For example, chatbots like Cortana and virtual assistants like Alexa are able to “understand” our questions and generate relevant answers thanks to the processing of high volumes of data, be it text data or voice recordings through machine learning.
These chatbots and virtual assistants use machine learning techniques to encode learning into mathema
Deep learning is all set to mark it digital impact across different domains and the job prospects are bright. As per a research by MarketsandMarkets, Artificial Intelligence, Machine Learning, and deep learning market is expected to grow to USD 11.4 billion by 2023.
For most of computing history, computers have been programmed with a set of coded rules to compute and make decisions. The progress powered by improvement in abstractions, hardware, and frameworks. That changes with Deep learning where computers can “learn” from the input data. For example, chatbots like Cortana and virtual assistants like Alexa are able to “understand” our questions and generate relevant answers thanks to the processing of high volumes of data, be it text data or voice recordings through machine learning.
These chatbots and virtual assistants use machine learning techniques to encode learning into mathematical models and make data predictions. The next level advancement in machine learning is Deep Learning, based on very deep and complex artificial neural networks that work towards emulating the human brain’s learning abilities to make the most accurate data predictions.
Definition - Deep Learning
Deep Learning is a subset of Artificial Intelligence. It carries out machine learning techniques and teaches logical functioning to computers using an artificial neural network composed of a number of levels arranged in a hierarchy. Since deep learning involves going deep into several layers of network, thus the name.
Learn more about the topic – What Is Deep Learning?
Deep Learning Courses Eligibility
Statistics and Math are the building blocks of deep learning, while the knowledge of programming would help you to understand the advanced concepts and topics of deep learning. Considering this, you must have a basic knowledge of complex math such as calculus, statistics, probability and linear algebra, and have a working knowledge of programming and programming languages, preferably Python.
You should have an undergraduate or a postgraduate degree in a relevant discipline, such as Mathematics, Statistics, Computer science, Information Management, etc. Some of the popular postgraduate qualifications are offered in subjects including Data Science, Business Analytics, Data Analytics, and Big Data, among others. Some deep learning roles may require prior experience in data science or artificial intelligence-specific roles.
How to Become a Deep Learning Engineer?
Deep learning is a very niche skill. To become a deep learning engineer, you should –
- Brush up your basic concepts of Math and Statistics, and learn linear algebra and basic calculus like functions, limits, differentiation, maxima, minima, etc.
- Learn about the basics of Natural Language Processing, Information Extraction, Computer Vision, Bioinformatics, Speech Processing, Optimization, Calculus, Information Theory and Decision Theory, etc.
- Learn to make smart decisions based on your data findings
- Learn about data structures, database design, data mining, distributed architecture, security applications, and applied systems analysis
- Develop a good command over programming languages like Python, R, Matlab, Julia and C++
- Take up deep learning courses or projects
Top Online Deep Learning Courses
- Deep Learning Nanodegree Program by UDACITY
- Neural Networks and Deep Learning by Coursera
- Deep Learning for Business by Coursera
- Deep Learning - Advanced Computer Vision (GANs, SSD, +More!) by UDEMY
- AI Capstone Project with Deep Learning by Coursera
- Deep Learning for Computer Vision by NPTEL
- Deep Learning Specialization by Coursera
- Applied AI with DeepLearning by Coursera
- Deep Learning A-Z - Hands-On Artificial Neural Networks by UDEMY
- Deep Learning by NPTEL
These deep learning courses would help you to learn the concepts, tools, and the intricacies of computer vision, natural language processing, neural networks, etc. Since deep learning has a high learning curve and offers an emerging market ahead, learning this skill can be very fruitful in future.
Deep Learning Skills
To start a career in deep learning, you should have the knowledge of –
- Programming languages (preferably Python/R)
- Statistical methods
- Python libraries like scikit-learn, pytorch
- Machine learning frameworks
- Hadoop & MapReduce
- Application Programming Interfaces (API)
- Data mining, cleaning and munging
- Data visualization and reporting techniques
Deep Learning Tools
Data analytics and visualization tools
- Tableau – A visual analytics platform for powerful data exploration and interactive visualization
- Pandas – An open source data analysis and manipulation tool
- Matplotlib - Python machine learning library for creating static, animated, and interactive visualizations
- Jupyter notebook – An open-source web application to create and share documents
Frameworks for general machine learning
- NumPy - An extension package for scientific computing with Python
- scikit-learn - A machine learning framework for predictive data analysis
- Natural Language Toolkit (NLTK) - Python-based human language data processing platform
Frameworks for neural network modeling
- TensorFlow – An open source platform for machine learning
- TensorBoard – A tool for measurements and visualizations in a machine learning workflow
- PyTorch - A library for Python programs to help build deep learning projects
- Keras – A lightweight, easy-to-use library for fast prototyping
- Caffe2 – A deep learning framework with mobile deployment support
Big data tools
- Apache Spark – A unified analytics engine for big data processing
- MemSQL – A relational database management system with a SQL interface
- Weka – A collection of machine learning algorithms used in data mining
Career Outlook - Deep Learning
Machine learning and deep learning technologies are being embraced by organizations of all sizes to enhance their products and services. Job opportunities are available across different sectors like internet technologies, software, cybersecurity, electronics, automobile, BFSI, security and defense, medical and manufacturing, among others.
Advance your career by learning deep learning technologies based on neural networks and how to implement them using frameworks like pytorch and tensorflow. Shiksha Online can help you discover the right course from top platforms and universities including Coursera, Edx, Udacity, NPTEL, MIT, Harvard, IITs, and IIMs. Compare prices, curriculum, projects, and reviews to choose the best course.
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Deep Learning Courses & Certifications Online
Commonly asked questions On Deep Learning Online Courses & Certifications
Yes. Deep Learning courses at an advanced level teach you about building, training, and optimization of AI models working on neural networks. You will learn how to use various machine learning algorithms, neural networking fundamentals, building and training multi-layered networks, model optimization, and deep learning tool frameworks.
Yes. A majority of the Deep Learning courses online provide you with certificates at the end of the course completion. From free course certificates to professional certificates, you can get it all. You just need to complete all your course modules and pass quizzes and practical assessments to get hold of the same. The Deep Learning certificates are highly valuable and add a lot of value to your work resume, leading to promising career opportunities.
Well, yes. Deep Learning certifications are highly valuable and are widely recognised by top companies in India. If you look at the recent employment reports, you will see that Deep Learning job postings have increased to a great extent because of the AI career boom in the market taking over almost every industry possible.
Having said that, it is important that the certification is from a reliable course provider for it to hold professional value. Some top Deep Learning certifications for you to explore are given here –
- Fundamentals of Deep Learning by Nvidia Deep Learning Institute (DLI)
- Certified Deep Learning Expert Certification by IABAC
- Deep Learning Specialization by DeepLearning.AI
- Deep Learning: Mastering Neural Networks by MIT xPRO
- IBM Machine Learning Professional Certificate
You can join Deep Learning courses online even if you do not have a technical background but have a lot of interest. You can start with foundational skills in math and statistics and programming languages like Python.
Feel free to explore a plethora of online courses in Deep learning that are available. From introductory modules for beginners to highly specialized, advanced level courses, you can learn it all. Take part in projects, workshops or internships to increase practical exposure and enhance your skill set gradually, turning out to be a strong asset for recruiters across industries.
Commonly asked questions On Deep Learning Online Courses & Certifications
A good amount of mathematical know-how of linear algebra, calculus, probability and statistics is important for building and managing complex deep learning models. For basic projects you can still manage with basic math knowledge but for advanced model applications and new developments it is important for you to have a solid grip on mathematical concepts.
Yes. Deep Learning coursework usually covers AI ethics and responsible use of deep learning for learners to be mindful of detecting and mitigating any possibility of bias in AI models. Further, it also covers ethical considerations throughout the AI lifecycle, from data collection to deployment. Since Deep Learning is the driving force of AI, it is important for professionals in the field to know about AI ethics and its responsible applications.
