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Home / Data Science and Deep Learning / AI & Deep Learning Course Training in USA
"The size of the North American market for Artificial Intelligence will be $29,000 million by 2025." - (Source). Huge investments and interest in Artificial Intelligence are expected to increase in the long run in the near future. As per McKinsey predictions, about 15% of vehicles will be fully automated in 2030. The number of startups based on AI in the US has increased by 114% between 2015 to 2018. By the latest advancements in Deep Learning, AI is being extensively used for search engines, virtual assistants, online translators, and many sales and marketing decisions. Tesla and Audi manufactured semi-autonomous cars and are working to improve to reach into full automated cars. AI is rapidly being adopted by many sectors and there is a demand for AI professionals.
Total Duration
2 Months
Prerequisites
The objective of this offering is to provide not only a conceptual understanding of the deep learning skills but also the practical applications in marketplace scenarios prevailing in the USA. This course serves as a perfect launchpad for professionals with an appreciation of statistics and knowledge of programming languages such as Python, R and RStudio into a career of AI and Deep Learning. Students will learn how to build AI applications, understand the ever-evolving neural network architectures, create AI algorithms, and minimize errors through advanced optimization techniques. By successfully graduating from this course, they will be able ready for careers in computer vision related image processing domains.
The field of Artificial Intelligence is morphing into an unstoppable force that the US-based companies are looking to capitalize on. This provides a tremendous opportunity for professionals to get into this market and command handsome salaries. The demand for AI professionals has grown by 29% from 2018 to 2019 and the average salary could be well over $100,000. This alone should be a prime motivating factor for professionals on the edge about whether to begin their careers in this hot domain. 360DigiTMG’s much researched and backed by industry experts, Artificial Intelligence training for students in the USA ensures that participants become seasoned practitioners in dealing with both structured and unstructured data. From this training, the students will learn concepts of Deep learning algorithms and Natural language processing.
Block Your Time
80 hours
Live Online Sessions
100 hours
Assignments
Live Projects
Who Should Sign Up?
360DigiTMG has instructors that are industry-leading experts in Machine Learning, Data Science, and related technologies. Artificial Intelligence and Deep Learning training course in the USA is delivered by 360DigiTMG. The main objective of this training is to provide a workforce and bridge the gap between business needs and talent. The module of the course is designed comprehensively by industry stalwarts. The module introduces Artificial Intelligence and Deep learning in neural networks. Students will learn Python libraries that include Keras, Tensor Flow, and OpenCV. The modules also cover different algorithms like perceptron and backpropagation. Learn Images processing and Computer vision data which is quite different from the regular tabular data and needs to be handled in a particular manner. Students also learn LSTMs that are particular types of RNNs. They have something called a ‘memory’ cell which ‘remembers’ information as it flows through the network. Hence this makes LSTMs best for forecasting type problems or any use case that has a temporal component. The modules also explain deeply about Reinforcement and Q-learning. This is different from supervised and unsupervised learning, which uses a concept called reinforcement. It builds upon the Markov Decision Process and builds an architecture that differs from both supervised and unsupervised approaches. Students will have the opportunity to build a chatbot from scratch. We start from a simple rules-based one to a more complex using NLP techniques. 360DigiTMG ensures that the students should gain a thorough knowledge of concepts and applications of statistical tools through hands-on experience. It also helps students to develop relevant skills that are required to grab lucrative jobs in giant companies.
The Perceptron Algorithm is defined based on a biological brain model. You will talk about the parameters used in the perceptron algorithm which is the foundation of developing much complex neural network models for AI applications. Understand the application of perceptron algorithms to classify binary data in a linearly separable scenario.
Neural Network is a black box technique used for deep learning models. Learn the logic of training and weights calculations using various parameters and their tuning. Understand the activation function and integration functions used in developing a Artificial Neural Network.
Learn about single-layered Perceptrons, Rosenblatt’s perceptron for weights and bias updation. You will understand the importance of learning rate and error. Walk through a toy example to understand the perceptron algorithm. Learn about the quadratic and spherical summation functions. Weights updating methods - Windrow-Hoff Learning Rule & Rosenblatt’s Perceptron.
Understand the difference between perception and MLP or ANN. Learn about error surface, challenges related to gradient descent and the practical issues related to deep learning. You will learn the implementation of MLP on MNIST dataset - multi class problem, IMDB dataset - binary classification problem, Reuters dataset - single labelled multi class classification problem and Boston Housing dataset - Regression Problem using Python and Keras.
Convolution Neural Network are the class of Deep Learning networks which are mostly applied on images. You will learn about ImageNet challenge, overview on ImageNet winning architectures, applications of CNN, problems of MLP with huge dataset.
You will understand convolution of filter on images, basic structure on convent, details about Convolution layer, Pooling layer, Fully Connected layer, Case study of AlexNet and few of the practical issues of CNN.
You will learn image processing techniques, noise reduction using moving average methods, different types of filters - smoothing the image by averaging, Gaussian filter and the disadvantages of correlation filters. You will learn about different types of filters, boundary effects, template matching, rate of change in the intensity detection, different types of noise, image sampling and interpolation techniques.
You will also learn about colors and intensity, affine transformation, projective transformation, embossing, erosion & dilation, vignette, histogram equalization, HAAR cascade for object detection, SIFT, SURF, FAST, BRIEF and seam carving.
Understand the language models for next word prediction, spell check, mobile auto-correct, speech recognition, and machine translation. You will learn the disadvantages of traditional models and MLP. Deep understanding of the architecture of RNN, RNN language model, backpropagation through time, types of RNN - one to one, one to many, many to one and many to many along with different examples for each type.
Faster object detection using YOLO models will be learnt along with setting up the environment. Learn pretrained models as well as building models from scratch.
Understand and implement Long Short-Term Memory, which is used to keep the information intact, unless the input makes them forget. You will also learn the components of LSTM - cell state, forget gate, input gate and the output gate along with the steps to process the information. Learn the difference between RNN and LSTM, Deep RNN and Deep LSTM and different terminologies. You will apply LSTM to build models for prediction.
Gated Recurrent Unit, a variant of LSTM solves this problem in RNN. You will learn the components of GRU and the steps to process the information.
You will learn about the components of Autoencoders, steps used to train the autoencoders to generate spatial vectors, types of autoencoders and generation of data using variational autoencoders. Understanding the architecture of RBM and the process involved in it.
You will learn the difference between CNN and DBN, architecture of deep belief networks, how greedy learning algorithms are used for training them and applications of DBN.
Understanding the generation of data using GAN, the architecture of the GAN - encoder and decoder, loss calculation and backpropagation, advantages and disadvantages of GAN.
You will learn to use SRGAN which uses the GAN to produce the high-resolution images from the low-resolution images. Understand about generators and discriminators.
You will learn Q-learning which is a type of reinforcement learning, exploiting using the creation of a Q table, randomly selecting an action using exploring and steps involved in learning a task by itself.
Learn to Build a speech to text and text to speech models. You will understand the steps to extract the structured speech data from a speech, convert that into text. Later use the unstructured text data to convert into speech.
Learn to Build a chatbot using generative models and retrieval models. We will understand RASA open-source and LSTM to build chatbots.
Learn the tools which automatically analyzes your data and generates candidate model pipelines customized for your predictive modeling problem.
Learn the methods and techniques which can explain the results and the solutions obtained by using deep learning algorithms.
A Large Language Model (LLM) in the context of data science typically refers to advanced natural language processing (NLP) models, which I am based on. These LLMs are designed to understand and generate human-like text, making them useful for a variety of data science tasks.
Generative AI, Diffusion Models, and Prompt Engineering are all related concepts in the field of artificial intelligence and natural language processing. Let me briefly explain each of them:
Playgrounds provide a sandbox-like setting where users can test different algorithms, models, and methodologies to gain insights and improve their skills.
DALL-E is a groundbreaking generative model in the field of data science and artificial intelligence, developed by OpenAI. The name "DALL-E" is a combination of the famous artist Salvador Dalí and the robot character WALL-E from the Pixar film.
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Artificial Intelligence is growing exponentially and its applications are used in every area of life. The AI is effecting and is going to significantly change and improve the process of work. Let’s peek into the latest trends of AI and Deep Learning. AI is playing a pivotal role in the Retail business. Amazon has efficiently started implementing AI technology in its physical stores. It has incorporated technology that is used in Self-driving cars including computer monitoring and deep learning processes in its business. The AI inbuilt tools help in detecting the products and getting them charged in an individual’s amazon account making the shopping experience worthwhile and easy for customers. Walmart has introduced using thousands of robots in its store replacing the human workforce. Apart from biometrics, facial recognition tools are driving a huge momentum in the market and going to be implemented very soon in many stores. By analyzing the facial expression while observing the various products, the personalized promotion of the products will be done by sensors observations.
As per the Mckinsey global institute predictions, by 2055 the robots will perform half of our work tasks which are repetitive and routine, making humans concentrate on creative works. For eg: JPMorgan Chase & Co. introduced COIN which means Contract Intelligence, based on AI. This COIN helps to analyze the commercial loan agreements in a fraction of seconds which is usually done by a team of lawyers for hours. This technology has reduced time, effort, and cost. AI and deep learning technologies are being used in Healthcare for diagnosis and treatment. IBM introduced an AI assistant named Watson, which is being used by many hospitals across the world in detecting cancer. AI tools are going to improve healthcare significantly in the coming years. AI chatbots became popular in a short time and are being used by many companies for an effective conversation with their customers leading to an increase in sales and production. AI and deep learning technologies are going to impact the world by reducing human errors and the workforce.
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"The training was organised properly, and our instructor was extremely conceptually sound. I enjoyed the interview preparation, and 360DigiTMG is to credit for my successful placement.”
Pavan Satya
Senior Software Engineer
"Although data sciences is a complex field, the course made it seem quite straightforward to me. This course's readings and tests were fantastic. This teacher was really beneficial. This university offers a wealth of information."
Chetan Reddy
Data Scientist
"The course's material and infrastructure are reliable. The majority of the time, they keep an eye on us. They actually assisted me in getting a job. I appreciated their help with placement. Excellent institution.”
Santosh Kumar
Business Intelligence Analyst
"Numerous advantages of the course. Thank you especially to my mentors. It feels wonderful to finally get to work.”
Kadar Nagole
"Excellent team and a good atmosphere. They truly did lead the way for me right away. My mentors are wonderful. The training materials are top-notch.”
Gowtham R
Data Engineer
"The instructors improved the sessions' interactivity and communicated well. The course has been fantastic.”
Wan Muhamad Taufik
Associate Data Scientist
"The instructors went above and beyond to allay our fears. They assigned us an enormous amount of work, including one very difficult live project. great location for studying.”
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AVP Technology
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The easiest way to understand the relationship between AI and Deep Learning is to visualise them as concentric circles. In that, AI is an idea that came first in which machines exhibit human intelligence. Machine Learning came next, which is an approach to achieve AI. And finally, Deep learning, which is driving today’s AI explosion, is a technique to implement Machine Learning.
While salaries of AI experts go up to US$ 1 million a year, it could start from US$ 150,000, on an average.
https://www.datamation.com/artificial-intelligence/ai-salaries.html
The salary range varies based on experience, industry, domain, geography and various other parameters. However, as a general rule of thumb, we can go with research conducted by job portals. On an average, in Malaysia, Machine learning professionals draw salaries of RM 165,074 per annum. Refer to ->
https://www.salaryexpert.com/salary/job/machine-learning-engineer/malaysia
On an average, Data scientist salaries are around RM 102,000 per annum.
If you miss a class, we will arrange for a recording of the session. You can then access it through the online Learning Management System.
We assign mentors to each student in this program. Additionally, during the mentorship session, if the mentor feels that you require additional assistance, you may be referred to another mentor or trainer.
The job roles in the field of Artificial Intelligence include Artificial Intelligence Developer, Artificial Intelligence Scientist, Artificial Intelligence Engineer, Artificial Intelligence & Machine Learning Engineer, etc.
The average salary for an AI Engineer in the US is up to $114,121, ranging from $77,000 to $151,000. The salary varies depending upon the experience and roles in the organizations.
Many projects are being carried out using AI and Deep learning tools in sectors that include Banking, Automation, Finance, and Healthcare.
Python, R, and RStudio are eminent statistical tools that help in deploying models. The applications of these statistical tools are very important for students who want to train in AI and Deep Learning.
360DigiTMG delivers training through both classrooms as well as online. The Online mode of learning is flexible and students can choose timings as per their schedule.
Artificial Intelligence technology is being adopted rapidly by many industries that include Manufacturing, Automation, Healthcare, Banking, Insurance, Education, Agriculture, Hotel, Finance, Retail, and many more.
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
Student Voices
4.8
I've reached a major milestone in my Data Analytics internship with 360DigiTMG. With guidance from experienced mentors, they’ve really helped me get closer to reaching my goals. Embrace the valuable knowledge and skills gained and continue leveraging this opportunity to excel in the dynamic field of data analytics.
I'm Sai Manikanta, delighted to share my internship journey at 360DigiTMG. This internship has been a great opportunity for me to expand my limits and gain new skills. Diverse activities provided profound insights, shaping a promising future. Grateful for this opportunity, I eagerly anticipate forthcoming outcomes.
The data analytics program was truly outstanding! The meticulously structured classes and enthusiastic instructors made learning both enjoyable and engaging. With this extensive knowledge at my disposal, I am not only confident but also eager to make significant strides in the field of data analytics.
One of the best institutes for training in Hyderabad. I am done with the Data science and Machine Learning course here. Trainers are highly educational and instructive. Invaluable experience gained through live projects, enhancing technical familiarity. Additional value provided through helpful working sessions further enriches the learning journey.
The teacher and staff are highly skilled at their jobs. They teach in a way that's easy to understand and interesting. They know a lot about the subject, so learning from them is great. The teacher plans everything well and explains hard stuff with lots of examples using Excel.
It was a wonderful experience for me as an intern to work in 360digitmg. This internship had made me become an expert in the field of data analytics which had greatly motivated me and Working with real-time datasets provided invaluable experience, enhancing my skills significantly.
It was an awesome experience at 360Digitmg, offering the best resources and fostering excellent interaction. Working on real-life projects under expert supervision provided invaluable learning opportunities. Overall, it was a highly rewarding learning experience that contributed significantly to my growth and career advancement.
I found a great coaching institute in Chennai for data-related courses. I completed a successful data analytics program there. The trainers were skilled and supportive, especially Vijay, who made learning Python easy. Thanks to him and 360DigiTMG. I also learned Data Analytics with SQL, Tableau, and Excel.
360DigiTMG institute offers an exceptional learning experience, excelling in data science and machine learning. Despite lacking coding background, tutors ensured effective learning, making concepts easily understandable. Tutorial sessions covered job interview prep and case studies, with Mind maps boosting confidence. Highly recommend this Bangalore institute for data-related courses.
Excited for upcoming internships, confident in my improved skills from the program. Explored new territories and gained invaluable experience. Ready to apply newfound knowledge and continue growing in future opportunities. Grateful for the journey so far, eager for what's ahead.
360DigiTMG institute offers one place where the course curriculum is so good and teacher training, equipping students with skills for their dream job. Grateful for the internship experience, including live projects, resume building, presentation practice, and interview preparation sessions. Enhanced confidence for future interviews. Thank you, 360DigiTMG, for the invaluable learning journey.
The data analytics with python course in the best coaching centre in Chennai. Finished the course well and worked on practical tasks. This helped me build my professional experience. By participating in interview preparation and project presentation sessions, I realized that I could present myself confidently to an interview.
During my internship at 360DigiTMG, I gained invaluable experience, expanding my knowledge significantly. The opportunity provided a rich learning environment, fostering personal and professional growth. Grateful for the wonderful experience and the skills acquired, which will undoubtedly shape my future endeavours.
Great institute! Exceptional learning experience, especially in data science and machine learning. Tutors adeptly simplified complex concepts despite my coding limitations. Varied tutorial sessions prepared us for job interviews with insightful case studies. Mind maps boosted confidence. Highly recommend this Bangalore-based institute for data-related courses.
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