$399.97 – $449.97

Multiple Dates

@AI Deep Learning PB-Scale 40-Node 2TB Big Data Cloud Boot Camp

Event Information

Share this event

Date and Time



Sofia University

1069 East Meadow Circle

Cafe of Bldg 1059 (Opposite to Main Entrance)

Palo Alto, CA 94303

View Map

Event description


Deep Learning PB-Scale 40-Node 2TB AI Big Data Cloud Boot Camp: Build & Operate Distributed AI Cluster w/t TensorFlow, Keras, Spark, Hadoop, Kafka, HDFS as well as Handwriting Recognition, Chatbot, TensorBoard Demos

You will work (Yes, build & operate) on a 40-node cluster with 2TB big data in total being capable to expand to PB-Scale druing 2 half-day hands-on sessions with 2 half-day lectures full of hindsight, insight and foresight nowhere you can find on the earth!

You must know DevOps, the merge of Software Developer and System Administrators in Cloud Era, but do you know the further merge of Data Scientist and Devops in AI Big Data Cloud Era - we call it DataDevOps?

It does not matter whether you are at senior-level or entry-level in Software Development/System Administration/Data Science/AI, as our advanced boot camps are brand new, with so called leap-frog effect, you are lucky to leap forward bypassing legacy technologies. The goal of the boot camp is to build & operate data pipeline and/or data lake for big data-enabled AI in cloud, and we will provide sample code in Python for Hadoop & TensorFlow and/or Scala for Spark (if you are new to them) for you to proceed and enhance and expand, your mileage may vary depending on your background and experiece, every attendee will benefit significantly

Fog Computing/Cloud Computing, Serverless Computing/Cloud-Native Computing, BlockChain/Bitcoin, Lambda Architecture, Cloud-Native Microservices-oriented Architecture/Monolithic architecture, Immutable Datalake, Real-time Data Pipeline, Container/VM/Bare Metal, IaaS/PaaS/SaaS, Machine Learning/Deep Learning, Supervised Learning/Unsupervised Learning, Big Data/Deep Learning, Hadoop/Spark, YARN/Mesos, Docker Engine/Kubernetes, OpenStack, SQL/NoSQL/HDFS, GUI/CLI/API, Hyper-scale/Hyper-convergence, SDN/NFV, GPU/CPU/TPU, File Storage/Object Storage/Block Storage, and much more. So are you feeling you are lost in the jungle of fast-pacing tech frontier? We Are Here to Help You to Get Out of It and Lead instead of Follow It!

You go to a lot of trainings and/or meetups, whether free or not, expensive or cheap, ALL of those are either marketing fluff, sales pitches, or short of global pictures, or short of details, no insight, let alone foresight. Our 2-day Boot Camp is radically different, vendor agnostic, no strings attached, full of meat, lots of hands-on, offering you both macro & micro perspective of the state-of-the-art in practical way with hindsight, insight and foresight!

We Don't Give You a Fish, Instead We Teach You to Fish

Topics include:

How to identify potential business use cases in leveraging big data container AI technology

How to obtain, clean, and combine disparate data sources to create a data pipeline for data lake
What Machine-Learning (Shallow Learning) & Deep Learning technique to use for a particular data science project

How to conduct PoC & productionalized big data projects in cloud/container cluster at scaleHow to create real-time data pipelines using the latest open source with public cloud or private cloud/container, ingest data in real time and at scale, process the data in real-time/interactive/batch, and build data products from real-time data sources

How to combines ETL, batch analytics, real-time stream analysis with machine learning, deep learning, and visualizations through both data pipeline & data lakes

Understand & master TensorFlow's fundamentals & capabilitiesExplore TensorBoard to debug and optimize your own Neural Network Architectures, train, test, validate & serve your models for real-life Deep Learning applications at Scale

Agenda (Subject to Change at Anytime without Notice) - 50% Lecture, 50% Hands-On, Vendor Agnostic, No Strings Attached, You Working on a Cluster instead of only an Instance in cloud, True PB-Scale Depends on Your Own Cloud Budget (could be outstanding) as opposed to Free Trial Limited Budget

Day 1
10:00 AM - 10:50AM Elastic Cloud Computing and Scalabe Big Data AI: What, Why and How?

11:00 AM - 11:50AM Deep Dive into Public/Private/Hybrid Cloud Infrastructure: Elastic/Plastic Cloud; Bare Metal/VM/Container; IaaS/PaaS/SaaS; Hyper-Scale/Hyper-Convergence; From Linux Kernel to Distributed System's CAP Theorem; OpenStack as the De facto Private Cloud; Capacity Planning & Auto-scaling Challenges of Cloud; Micro-service-based Immutable Architecture

12:00 AM - 12:50AM Deep Dive into Big Data Technology Stack: Nature of Big Data - Structural/Unstructural; Hot/Warm/Cold; Machine/Human; Text/Numerical, SQL(ACID)/NoSQL(BASE); Batch(Hindsight)/Interactive (Insight)/Streaming(Foresight); Data Pipeline & Datalake; Hadoop/Spark/Kafka/HDFS/HBase/HIVE/ZooKeeper

1:00 PM - 1:50M Lunch Session (Lunch included, Veggie option available): Google/AWS Cloud|Docker/CoreOS Container In-Depth: Computation/Storage/Networking Models

2:00PM - 6PM Hands-on I: I Set Up & Test Drive Your Own AI Big Data Google Cloud Cluster (Hadoop, Spark, Kafka, HDFS, Tensorflow) : Using Spark/Hadoop for Word Counting & Sentiment Analysis (for Advanced Attendees only) of Twitter Data/Kafka Stream of system logs

Day 2
10:00 AM - 10:50AM Practical Machine Learning In-Depth: Feature Engineering, From Regression to Classification, 5 Tribes of Machine Learning: Symbolists with Inverse Deduction of Symbolic Logic, Connectionists with Backpropagation of Neural Networks, Evolutionaries with Genetic Programming, Bayesians with Probabilistic Inference in Statistics, Analogizers with Support Vector Machines; Supervised Learning (Classification/Regression), Unsupervised Learning (Clustering), Semi-Supervised Learning; Data Ingestion & Its Challenges, Data Cleansing/Prep-processing; Training Set/Testing Set Partitioning; Feature Engineering (Feature Extraction/Selection/Construction/Learning, Dimension Reduction); Model Building/Evaluation/Deployment|Serving/Scaling|Reduction/Optimization with Prediction Feedbacks

11:00 AM - 11:50AM Practical Deep-Learning-based AI In-Depth: Weak/Special AI vs Strong/General AI; Key Components of AI: Knowledge Representation, Deduction, Reasoning, NLP, Planning, Learning,Perception, Sensing & Actuation, Goals & Problem Solving, Consciousness & Creativity; Rectangle of Deep Learning, Shallow Learning, Supervised Learning, and Unsupervised Learning; Basic Multi-layer Architecture of Deep Forward/Convolutional Neural Networks(FNN/CNN)/Deep Recurrent Neural Networks(RNN)/Long short-term memory(LSTM): Input/Hidden/Output Layers, Weights, Biases, Activation Function, Feedback Loops, Backpropagation from Automatic Differentiation and Stochastic Gradient Descent (SGD); Convex/Non-Convex Optimization; Ways of Training Deep Neural Networks: Data/Model Parallelism, Synchronous/Asynchronous Training, Variants of SGD, Gradient Vanishing/Explotion, Loss Function Minimization/Optimization with Dropout/Regulariztion & Batch Normalization & Learning Rate & Training Steps, and Unsupervised Pre-training (Autoencoder etc.); Deep Learning Applications - What's Fit and What's Not?: Deep Structures, Unusual RNN, Huge Models

12:00 AM - 12:50PM Embracing Paradigm Shifting from Algorithm-based Rigid Computing to Model-based Big Data Cloud IoT-powered Deep Learning AI for Real-Life Problem Solving: What, Why and How? - Problem Formulation, Data Gathering, Algorithmic & Neural Network Architecture Selection, Hyperparameter Turning, Deep Learning, Cross Validation, and Model Serving

1:00 PM - 1:50PM Lunch Session (Lunch included, Veggie option available) - Tensorflow In-Depth: The Origin, Fundamental Concepts (Tensors/Data Flow Graph & More), Historical Development & Theoretical Foundation; Two Major Deep Learning Models and Their TensorFlow Implementation: Convolutional Neural Network (CNN), Recurrent Neural Network (RNN); GPU/Tensorflow vs. CPU/NumPy; TensorFlow vs Other Open Source Deep Learning Packages: Torch, Caffe, MXNet, Theano: Programming vs. Configuration; Tackling Deep Learning Blackbox Puzzle with TensorBoard

2:00PM - 6PM Hands-on I Continued: I Set Up & Test Drive Your Own AI Big Data Google Cloud Cluster (Hadoop, Spark, Kafka, HDFS, HBASE, HIVE, Zookeeper, Tensorflow) : Using Spark/Hadoop for Word Counting & Sentiment Analysis (for Advanced Attendees only) of Twitter Data/Kafka Stream of system logs

Hands-on II (For Advanced Attendeeds only): Build, Train & Serve Your Own Chosen AI Application Using Python in Your Own Scalable AI Big Data Google Cloud| Cluster (TensorFlow, Spark, Hadoop, Kafka, HBase, HIVE, Zookeeper)

Who Should Attend:

CEO, SVP/VP, C-Level, Director, Global Head, Manager, Decision-makers, Business Executives, Analysts, Project managers, Analytics managers, Data Scientist, Statistian, Sales, Marketing, human resources, Engineers, Developers, Architects, Networking specialists, Students, Professional Services, Data Analyst, BI Developer/Architect, QA, Performance Engineers, Data Warehouse Professional, Sales, Pre Sales, Technical Marketing, PM, Teaching Staff, Delivery Manager and other line-of-business executives

Statisticians, Big Data Engineer, Data Scientists, Business Intelligence professionals, Teaching Staffs, Delivery Managers, Product Managers, Cloud Operaters, Devops, System admins, Business Analysts, Financial Analysts, Solution Architects, Pre-sales, Sales, Post-Sales, Marketers, Project Managers, and Big Data Cloud AI Enthusiasts.

Hands-on Requirements:
1) Each student should bring their own 64bit Linux-based or Windows with Putty installed laptop (no VM required as we are using cloud) with Minimum 2GB RAM and Free 200GB hard disk with administrative/root privileges and wireless connectivity.

2) Google/ Cloud account ready

3) It's better but not necessry to bring your own WiFi hotspot as we have wifi for you

4) Bash & Python skills welcome but not required

For Corporates, why you should send your employees to our Unique Second-to-None AI Big Data Cloud Boot Camp?
- Front-runner Practitioner in AI Big Data Cloud Automation with rich industry experience provide the training
- Be capable and willing to customize our boot camp to meet your corporates' specific needs
- Detail-oriented, heavy hands-on, you can send a team or invite us for a private onsite group boot camp
- Potential partnership opportunities

For Individuals, why you should sign up our Unique Second-to-None AI Big Data Cloud Boot Camp even without a corporate sponsorship?
- Front-runner Practitioner in AI Big Data Cloud Automation with rich industry experience provide the training
- Be capable and willing to personalize our boot camp to match your individual background and interests during hands-on sessions
- Detail-oriented, heavy hands-on, you set your pace, make your own choice
- Great networking and career advance opportunities

Share with friends


Sofia University

1069 East Meadow Circle

Cafe of Bldg 1059 (Opposite to Main Entrance)

Palo Alto, CA 94303

View Map

Save This Event

Event Saved