Artificial Intelligence Course in San Francisco, CA


Artificial Intelligence Course in San Francisco, CA

Flexible Schedule

48 Hrs Project Work & Exercises

32 Hrs Instructor Led online Training

24 Hrs Self-paced Videos

24X7 Support

Certification and Job Assistance

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4.9 out of 1387+ Ratings
ZebLearn Artificial Intelligence course in San Francisco is an industry-designed course for learning TensorFlow, artificial neural network, perceptron in neural network, transfer learning in machine learning, backpropagation for training networks through hands-on projects and case studies. Get the best online Artificial Intelligence training in San Francisco from Artificial Intelligence certified experts. This is created in collaboration with IBM.


ZebLearn offers one of the best AI courses in San Francisco, Illinois that will help you master deep learning, building artificial neural network, various layers and components of artificial neural networks, supervised, unsupervised and reinforcement learning methodologies through hands-on projects and case studies.

  • The building blocks of Deep Learning
  • Various types of neural networks
  • Using backpropagation for training networks
  • Introducing the TensorFlow for computation
  • Recurrent and convolutional neural network
  • Python scripting in machine learning
  • Real world applications of Artificial Intelligence.
  • Professionals in analytics, data science domains, ecommerce, search engine domains
  • Software professionals looking for a career switch and fresh graduates.
Anybody can take this Training Course regardless of their prior skills.
San Francisco is one of the biggest cities in the United States of America. It is home to a large number of enterprises in the domains of manufacturing, logistics, technology, technology and others. All these industries are heavily invested in AI making it a lucrative market for AI jobs.
San Francisco is rising rapidly thanks to its vibrant economy and the huge impetus given by the state and local government bodies along with industry organizations to embrace top technologies to propel the economy forward. Thus the market trend for AI in San Francisco is rising rapidly.
Today, Artificial Intelligence has conquered almost every industry. Within a year or two, nearly 80% of emerging technologies will be based on AI. Machine Learning, especially Deep Learning, which is the most important aspect of Artificial intelligence, is used from AI-powered recommender systems (Chatbots) and Search engines for online movie recommendations. Therefore, to remain relevant and gain expertise in this emerging technology, enroll in ZebLearn’s AI Course.

Here are a few reasons why Artificial Intelligence is a great career option:

  • There are over 35,000 job opportunities available for AI professionals in the United States alone – LinkedIn
  • AI Engineers earn over US$114k per annum in the United States – Glassdoor

This will help you build a solid AI career and get the best artificial intelligence engineer positions in leading organizations.

What you will gain?

  • 1 to 1 Live Online Training
  • Dedicated 24 x 7 Support
  • Flexible Class Timing
  • Training Completion Certification
  • Direct Access to the Trainer
  • Lifetime Access of an LMS
  • Real-time Projects
  • Dedicated Placement Support


Self Paced Training

45 Hrs e-learning videos
Lifetime Free Upgrade
24×7 Lifetime Support & Access


Online Live One to One Training

Everything in self-paced, plus
45 Hrs of Instructor-led Training
1:1 Doubt Resolution Sessions
Attend as many batches for Lifetime


Course Content

  • 1.1 Field of machine learning, its impact on the field of artificial intelligence
  • 1.2 The benefits of machine learning w.r.t. Traditional methodologies
  • 1.3 Deep learning introduction and how it is different from all other machine learning methods
  • 1.4 Classification and regression in supervised learning
  • 1.5 Clustering and association in unsupervised learning, algorithms that are used in these categories
  • 1.6 Introduction to ai and neural networks
  • 1.7 Machine learning concepts
  • 1.8 Supervised learning with neural networks
  • 1.9 Fundamentals of statistics, hypothesis testing, probability distributions, and hidden markov models.
  • 2.1 Multi-layer network introduction, regularization, deep neural networks
  • 2.2 Multi-layer perceptron
  • 2.3 Overfitting and capacity
  • 2.4 Neural network hyperparameters, logic gates
  • 2.5 Different activation functions used in neural networks, including relu, softmax, sigmoid and hyperbolic functions
  • 2.6 Back propagation, forward propagation, convergence, hyperparameters, and overfitting.
  • 3.1 Various methods that are used to train artificial neural networks
  • 3.2 Perceptron learning rule, gradient descent rule, tuning the learning rate, regularization techniques, optimization techniques
  • 3.3 Stochastic process, vanishing gradients, transfer learning, regression techniques,
  • 3.4 Lasso l1 and ridge l2, unsupervised pre-training, xavier initialization.
  • 4.1 Understanding how deep learning works
  • 4.2 Activation functions, illustrating perceptron, perceptron training
  • 4.3 multi-layer perceptron, key parameters of perceptron;
  • 4.4 Tensorflow introduction and its open-source software library that is used to design, create and train
  • 4.5 Deep learning models followed by google’s tensor processing unit (tpu) programmable ai
  • 4.6 Python libraries in tensorflow, code basics, variables, constants, placeholders
  • 4.7 Graph visualization, use-case implementation, keras, and more.
  • 5.1 Keras high-level neural network for working on top of tensorflow
  • 5.2 Defining complex multi-output models
  • 5.3 Composing models using keras
  • 5.3 Sequential and functional composition, batch normalization
  • 5.4 Deploying keras with tensorboard, and neural network training process customization.
  • 6.1 Using tflearn api to implement neural networks
  • 6.2 Defining and composing models, and deploying tensorboard
  • 7.1 Mapping the human mind with deep neural networks (dnns)
  • 7.2 Several building blocks of artificial neural networks (anns)
  • 7.3 The architecture of dnn and its building blocks
  • 7.4 Reinforcement learning in dnn concepts, various parameters, layers, and optimization algorithms in dnn, and activation functions.
  • 8.1 What is a convolutional neural network?
  • 8.2 Understanding the architecture and use-cases of cnn
  • 8.3‘What is a pooling layer?’ how to visualize using cnn
  • 8.4 How to fine-tune a convolutional neural network
  • 8.5 What is transfer learning?
  • 8.6 Understanding recurrent neural networks, kernel filter, feature maps, and pooling, and deploying convolutional neural networks in tensorflow.
  • 9.1 Introduction to the rnn model
  • 9.2 Use cases of rnn, modeling sequences
  • 9.3 Rnns with back propagation
  • 9.4 Long short-term memory (lstm)
  • 9.5 Recursive neural tensor network theory, the basic rnn cell, unfolded rnn, dynamic rnn
  • 9.6 Time-series predictions.
  • 10.1 Gpu’s introduction, ‘how are they different from cpus?,’ the significance of gpus
  • 10.2 Deep learning networks, forward pass and backward pass training techniques
  • 10.3 Gpu constituent with simpler core and concurrent hardware
  • 11.1 Introduction rbm and autoencoders
  • 11.2 Deploying rbm for deep neural networks, using rbm for collaborative filtering
  • 11.3 Autoencoders features and applications of autoencoders.
  • 12.1 Image processing
  • 12.2 Natural language processing (nlp) – Speech recognition, and video analytics.
  • 13.1 Automated conversation bots leveraging any of the following descriptive techniques: Ibm watson, Microsoft’s luis, Open–closed domain bots,
  • 13.2 Generative model, and the sequence to sequence model (lstm).

Benefits of Online Training

  •  100% Satisfaction Ratio
  •  Dedicated Help In Global Examination
  •  Updated Syllabus & On-Demand Doubt Session
  •  Special Group & Corporate Discounts


Our Artificial Intelligence online training involves the simultaneous participation of both learners and instructors in an online environment. Being a learner, you can log in to our applied AI course sessions from anywhere and attend the class without having to be present physically. Also, we record the proceedings of all AI classes and equip you with them to further enhance your learning process. On the completion of this AI training online, your experience will be equivalent to that of a professional who has worked for 6 months in the industry.
At ZebLearn, you can enroll in either the instructor-led online training or self-paced training. Apart from this, ZebLearn also offers corporate training for organizations to upskill their workforce. All trainers at ZebLearn have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.
ZebLearn is offering the 24/7 query resolution, and you can raise a ticket with the dedicated support team at anytime. You can avail of the email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our trainers.

You would be glad to know that you can contact ZebLearn support even after the completion of the training. We also do not put a limit on the number of tickets you can raise for query resolution and doubt clearance.

ZebLearn is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

ZebLearn actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.
You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.
Once you complete ZebLearn’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded ZebLearn’s course completion certificate. This certificate is very well recognized in ZebLearn-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.
Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

Recently Trained Students

Jessica Biel

– Infosys

My instructor had sound Knowledge and used to puts a lot of effort that made the course as simple and easy as possible. I was aiming for with the help of the ZebLearn Online training imparted to me by this organization.

Richard Harris


I got my training from Gaurav sir, I would like to say that say he is one of the best trainers. He has not even trained me but also motivated me to explore more and the way he executed the project, in the end, was mind-blowing.

Job Opportunities

According to Gartner, AI is heralded to create 2.3 million jobs by the end of 2020, leading a net gain of 500,000 potentially new jobs. And in the light of COVID-19 crisis, job opportunities for AI workers are bound to see a sharp rise.

The global economic status is not the same, but AI talents can remain positive.
According to International Data Corporation (IDC), the number of AI jobs is expected to globally grow 16 percent this year.

Gartner’s report also mentions 85 percent of AI professionals believe the industry has become more diversified in recent years.

Know more

Job Designation

  • Data Scientist
  • Computer Science & AI Research
  • Machine Learning Scientist
  • Computer Science & AI Research
  • Natural Language Processing
  • Data Analytics

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