Training is not a commodity – all training centres are not the same. Iverson Associates Sdn Bhd is the most established, the most reputable, and the top professional IT training provider in Malaysia. With a large pool of experienced and certified trainers, state-of-the-art facilities, and well-designed courseware, Iverson offers superior training, a more impactful learning experience and highly effective results.
At Iverson, our focus is on providing high-quality IT training to corporate customers, meeting their learning needs and helping them to achieve their training objectives. Iverson has the flexibility to provide training solutions whether for a single individual or the largest corporation in a well-paced or accelerated training programme.
Our courses continue to evolve along with the fast-changing technological advances. Our instructor-led training services are available on a public and a private (in-company) basis. Some of our courses are also available as online, on demand, and hybrid training.
This course builds on skills developed in the Data Science and Big Data Analytics course. The main focus areas cover Hadoop (including Pig, Hive, and HBase), Natural Language Processing, Social Network Analysis, Simulation, Random Forests, Multinomial Logistic Regression, and Data Visualization. Taking an “Open” or technology-neutral approach, this course utilizes several open-source tools to address big data challenges
4-8 Mar 2024
24-28 Jun 2024
23-27 Sep 2024
This course is intended for aspiring Data Scientists, data analysts that have completed the associate level Data Science and Big Data Analytics course, and computer scientists wanting to learn MapReduce and methods for analyzing unstructured data such as text
Upon successful completion of this course, participants should be able to:
Lesson 1: The MapReduce Framework
Lesson 2: Apache Hadoop
Lesson 3: Hadoop Distributed File System
Lesson 4: YARN
Lesson 1: Hadoop Ecosystem
Lesson 2: Pig
Lesson 3: Hive
Lesson 4: NoSQL - Not Only SQL
Lesson 5: HBase
Lesson 6: Spark
Lesson 1: Introduction to NLP
Lesson 2: Text Preprocessing
Lesson 3: TFIDF
Lesson 4: Beyond Bag of Words
Lesson 5: Language Modeling
Lesson 6: POS Tagging and HMM
Lesson 7: Sentiment Analysis and Topic Modeling
Lesson 1: Introduction to SNA and Graph Theory
Lesson 2: Most Important Nodes
Lesson 3: Communities and Small World
Lesson 4: Network Problems and SNA Tools
Lesson 1: Simulation
Lesson 2: Random Forests
Lesson 3: Multinomial Logistic Regression
Lesson 1: Perception and Visualization
Lesson 2: Visualization of Multivariate Data
This course provides practical foundation level training that enables immediate and effective participation in Big Data and other analytics projects. It includes an introduction to Big Data and the data analytics lifecycle to address business challenges that leverage Big Data.
The course provides grounding in basic and advanced analytic methods and an introduction to Big Data analytics technology and tools, including MapReduce and Hadoop. Labs offer opportunities for students to understand how these methods and tools may be applied to real world business challenges by a practicing data scientist.
The course takes an “open”, or technology-neutral approach and includes a final lab which addresses a big data analytics challenge by applying the concepts taught in the course in the context of the data analytics lifecycle. The course prepares the student for the Dell EMC Proven™ Professional Data Scientist Associate (DCA-DS) certification exam.
22-26 Jan 2024
26 Feb 2024 - 1 Mar 2024
11-15 Mar 2024 (Penang Date)
3-7 Jun 2024
9-13 Sep 2024
14-18 Oct 2024 (Penang Date)
16-20 Dec 2024
This course is intended for individuals seeking to develop an understanding of Data Science from the perspective of a practicing Data Scientist, including:
To complete this course successfully and gain the maximum benefits from it, a student should have the following knowledge and skill sets:
Upon successful completion of this course, participants should be able to:
In addition to lecture and demonstrations, this course includes labs designed to allow practical experience for the participant.