François Chung, Ph.D.

Tag: cognitive class

Deep learning and TensorFlow

Deep learning and TensorFlow

Cognitive Class training, MOOC (2020). This learning path presents the basic concepts of deep learning and TensorFlow with hands-on experience in solving problems. Throughout the training, TensorFlow is used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the deep learning world where TensorFlow is applied for backpropagation to tune the weights and biases while the neural networks are being trained.

Course 1: Deep learning fundamentals

Main topics:

  • Introduction to deep learning;
  • Deep learning models;
  • Additional deep learning models;
  • Deep learning platforms and libraries.

Course 2: Deep learning with TensorFlow

Main topics:

  • Introduction to TensorFlow;
  • CNN - Convolutional Neural Network;
  • RNN - Recurrent Neural Network;
  • Unsupervised learning.

References

Training

Deep learning fundamentals (course certificate)
Deep Learning Essentials (certification badge)
Deep learning with TensorFlow (course certificate)
Deep Learning using TensorFlow (certification badge)

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Spark fundamentals

Spark fundamentals

Cognitive Class training, MOOC (2020). This learning path addresses the fundamentals of Apache Spark, an open source engine for large scale data processing that is revolutionizing the analytics and big data world. This training is an opportunity to learn from industry leaders about Spark, which is built around speed, ease of use and analytics, and provides hands-on opportunities and projects to build confidence with the Spark toolset.

Course 1: Spark fundamentals I

Main topics:

  • Introduction to Spark;
  • Resilient Distributed Dataset (RDD) and DataFrames;
  • Spark application programming;
  • Introduction to Spark libraries;
  • Spark configuration, monitoring and tuning.

Course 2: Spark fundamentals II

Main topics:

  • Introduction to notebooks;
  • RDD architecture;
  • Optimizing transformations and actions;
  • Caching and serialization;
  • Developing and testing.

Course 3: Spark MLlib

Main topics:

  • Spark MLlib data types;
  • Review of algorithms;
  • Decision trees and random forests;
  • Spark MLlib clustering.

Course 4: Exploring GraphX

Main topics:

  • Introduction to Graph-Parallel;
  • Exploring graph operators;
  • Visualizing and modifying GraphX;
  • Aggregation and caching.

Course 5: Big data in R using Spark

Main topics:

  • Introduction to SparkR;
  • Data manipulation in SparkR;
  • Machine learning in SparkR.

References

Training

Spark fundamentals I (course certificate)
Spark – Level 1 (certification badge)
Spark fundamentals II (course certificate)
Spark MLlib (course certificate)
Exploring GraphX (course certificate)
Big data in R using Spark (course certificate)
Spark - Level 2 (certification badge)

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Hadoop fundamentals (Cognitive Class training)
Data science specialization (Coursera training)

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Hadoop fundamentals

Hadoop fundamentals

Cognitive Class training, MOOC (2020). This learning path presents Hadoop, which is an open source framework for distributed storage and processing of big data. The training covers content that is critical to anyone's success in this realm by explaining the Hadoop conceptual design, introducing MapReduce, YARN (Yet Another Resource Negotiator) and Hive, then explaining how to use Hadoop and manipulate data without the use of complex coding.

Course 1: Hadoop 101

Main topics:

  • Introduction to Hadoop;
  • Hadoop architecture and HDFS;
  • Hadoop administration;
  • Hadoop components.

Course 2: MapReduce and YARN

Main topics:

  • Introduction to MapReduce and YARN;
  • Limitations of Hadoop v1 and MapReduce v1;
  • YARN architecture.

Course 3: Moving data into Hadoop

Main topics:

  • Load scenarios;
  • Using Sqoop;
  • Flume overview;
  • Using Data Click.

Course 4: Accessing Hadoop data using Hive

Main topics:

  • Introduction to Hive;
  • Hive DDL - Data Definition Language;
  • Hive DML - Data Manipulation Language;
  • Hive operators and functions.

References

Training

Hadoop 101 (course certificate)
Hadoop Foundations – Level 1 (certification badge)
MapReduce and YARN (course certificate)
Hadoop Programming – Level 1 (certification badge)
Moving data into Hadoop (course certificate)
Hadoop Administration – Level 1 (certification badge)
Accessing Hadoop data using Hive (course certificate)
Hadoop Data Access – Level 1 (certification badge)
Hadoop Foundations – Level 2 (certification badge)

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Spark fundamentals (Cognitive Class training)
Data science specialization (Coursera training)

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Blockchain essentials

Blockchain essentials

Cognitive Class training, MOOC (2020). This online training presents blockchain for business and explores use cases that demonstrate how this technology is radically improving supply chains and banking, as well as creating new opportunities for innovation. Blockchain technology provides a shared ledger to save time when recording transactions between parties, remove costs associated with intermediaries and reduce risks of fraud and tampering.

Module 1: What is blockchain?

Main topics:

  • Business networks;
  • Ledgers, transactions and contracts;
  • The problem with existing networks;
  • Different types of blockchain;
  • Requirements of a blockchain for business.

Module 2: Examples of blockchain networks

Main topics:

  • Improving global trade;
  • Supply chain transparency;
  • Global payments;
  • Decentralized and trusted identity;
  • Key players for blockchain adoption.

Module 3: IBM and blockchain

Main topics:

  • IBM's blockchain strategy;
  • IBM Blockchain Platform;
  • Hyperledger project;
  • Hyperledger Fabric.

References

Training

Blockchain essentials (course certificate)
IBM Blockchain Essentials V2 (certification badge)

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