Deep Learning Courses - Plan Your Dream Job Now

Deep Learning is one of the most popular and promising career choices. LinkedIn's Emerging Jobs India Report finds that artificial intelligence specialists will be one of the most sought-after titles in 2020. It is the top emerging job in the US. Deep Learning is a machine learning technique, where you learn by example, like a human brain. From driverless cars to home assistance devices, deep learning algorithms have penetrated every walks of life. It allows machines to solve a complex problem using a data set that is very diverse and unstructured. Chatbots, housekeeping robots, resume screening, CRM systems, medical research for cancer patients, etc are some of the examples where extensive use of deep learning algorithms is used.



Deep Learning Courses
Deep Learning Courses


Future Of Deep Learning


The future of Machine Learning looks promising. There is an urgent need for professionals who are trained in Deep Learning jobs. Marks and Spencer, one of the biggest retail brands in the UK, has observed a decrease in 50% store call volume using Google Cloud's Contact Center AI. 75% of Netflix users select films from the recommendation given by using these algorithms. McKinsey's report suggests that by 2030, some 70% of companies might have adopted at least one type of AI technology.


Best Deep Learning Courses


Stanford University offers the best courses in Deep Learning. Deep Learning specialization course by the Standford Professor and AI expert, Andrew Ng in Coursera, has the highest ratings. You will learn the basics of Deep Learning and understand how to build neural networks. A certificate is also provided on completion. Financial Aids are also available for the course. 


Python language, deep learning framework, and Tensorflow are used to practice case studies. Tensorflow is a low-level API developed by Google to make numerical computations faster and to implement neural networks. Udacity's Intro to TensorFlow for deep learning is one of the best courses to learn Tensorflow. 


Stanford also offers specialized coursed like CS231n for computer Vision and CS224d for NLP. CS231n is a 10-week course where you will learn to implement, train, and debug neural networks and gain a detailed understanding of cutting-edge research in computer vision. You may also earn a Professional Certificate on completion. You are expected to commit 8-12 hours/week for the duration of the program. Complete lecture videos are available for free on the Stanford Online Hub and the YouTube channel. 


IIT Roorkee also offers a 2.5 months live-online instructor-led certificate course on AI/Deep Learning. Kiril Eremenko's deep learning course on Udemy includes both Python and R code templates for you to download and use on your projects. His clear and concise explanations have made him one of the best instructors on Udemy. A solid background in Mathematics and statistics is a big advantage for you. Statistics, Linear Algebra, and Calculus concepts are frequently used in DL.



Machine Learning Job Roles


Machine learning engineer 


As an ML engineer, you will use algorithms and neural networks to build usable solutions for business. You have to design and implement Machine Learning applications/algorithms such as clustering, anomaly detection, classification, or prediction to address business challenges. You will be responsible for supporting the Data Scientist in experimenting with data modeling and prototyping.


Skills Required - Python, Java, Scala, Docker containers, Spark, Kubernetes, Keras/Tensorflow, ML concepts.


Data Scientist


In this role, you are responsible for data mining, pre-processing, and statistical analysis of data. You will build and train models to address business requirements and present information using data visualization techniques. You will be responsible for designing, writing code, refactoring the code, or create services required by the business. 


Skill Required - Python, R, MATLAB, SQL, Machine learning techniques and algorithms, such as neural network, Deep learning, linear algebra, and statistical analysis.


Data Analyst


Data Analysts primarily focus on interpreting data and convert it into such information that can be used to improve business decisions and strategies. You have to identify the hidden patterns and trends within large datasets and aid businesses in using those insights to make sound business decisions.


Skills Required - ETL tools, Hadoop based Analytics, Strong background in Maths and Statistics, ML, Programming.


Computer Vision Engineer 


In this role, you automate tasks that the human visual system can do. You will develop scripts and applications that use computer vision to identify and position certain objects for robots to pick and place. 


Skills Required - Computer Vision, Deep Learning, TensorFlow, CNN, RNN, Object detection techniques such as EfficientNet, YOLO v3, Mobilenet SSD, Retina SSD.


NLP Scientist


NLP is a field of Artificial Intelligence that gives the machines the ability to derive meaning from human languages. As an NLP scientist, you transform natural language data into useful features using natural language processing techniques to feed classification algorithms.


Skills Required - NLP frameworks like Spacy, fastText. nltk, scikit, Machine Learning techniques, Deep Learning frameworks like Keras and Tensorflow, Python.


Top Career Path in Deep Learning


The average salary of a deep learning engineer in the United States is $178,463 per year. In India, they earn ₹1,099K / yr. Big firms like Google, Amazon, Facebook, Deloitte, IBM, Accenture, LinkedIn, Citrix, Flipkart, and Myntra, recruit for various ML positions including Machine Learning Engineer, Machine Learning Analyst, Data Scientist, NLP Data Scientist, Data Analyst, Research Engineer, to name a few. A PWC survey of Indian businesses found that 74 percent believe AI will improve economic growth, cybersecurity, global health, and education.

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