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HRDF Approved Training Provider in Malaysia - Modular Fast Track Skill-Based Trainings

Python Machine Learning with Scikit Learn Training

Scikit Learn is the de facto Machine Learning package for Python. It consists of classification, regression, clustering, dimension reduction, model selection, and many data preprocessing functionalities. You can do many supervised and unsupervised machine learning with Scikit Learn. This Scikit Learning training aims to equip you with basic machine learning knowledge using such as classification, regression, clustering, PCA, ensemble methods, and neural networks. The topics include:

  • Linear regression
  • Create representations of documents and images that can be used in machine learning models
  • Discover hidden structures in data using clustering and PCA
  • Basics of Neural Network

 

HRDF SBL Claimable for Employers Registered with HRDF

HRDF claimable

Course Code: M268

Course Booking

MYR880.00

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Course Details

Module 1 Getting Started on Scikit-Learn

  • What is Scikit Learn
  • Scikit Learn Applications
  • Installing Scikit-Learn

Module 2 Classification

  • What is Classification
  • Classifier Algorithms
  • Classification Steps
  • Ensemble Classifiers
  • Save and Load Models
  • Confusion Matrix
  • Classification Metrics - Precision, Recall, F1 Score

Module 3 Regression

  • What is Regression
  • Regression Algorithms
  • Linear Regression
  • Multivariate Regression

Module 4 Clustering

  • What is Clustering
  • Clustering Algorithms

Module 5 Dimension Reduction

  • Principal Component Analysis

Module 6 Neural Network

  • What is Neural Network?
  • Multi Layer Perceptron Classifier
  • Activation Functions and Solvers

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Financial Analysts
  • Digital Marketers

Prerequisite

Prerequisite

This is a intermediate level course. The following prerequisite is assumed

Software Requirement

Pls download and install the following software prior to the class

Trainers

Scikit Learn TrainerDr. Aanand is a Full Stack Data Scientist who once had a torrid love affair with Physics. He has consulted and published in the area of Public Health, Electricity Markets, Telecom, BFSI, Advertising & Communication Strategies and Digital & Social Media Technologies. He has worked on assignments with international agencies such as International Monetary Fund, World Bank, Royal Netherland Embassy etc. besides MNCs like Tata Consultancy Services, Kie Square Consulting and several government organizations of national importance. He regularly conducts general training programs in Python (Pandas, NumPy, SciPy, Matplotlib, Bokeh), R (dplyr, rstanarm, knitR, ggplot2), Data Visualization (Tableau, D3.js) and Machine Learning (Reinforced Learning, Scikit Learn) and specialized training programs on Structural Equation Modeling and SAP Hana. He holds a doctorate in Operations Research from Indian Institute of Management Ahmedabad and a post-graduate in Physics from University of Mumbai. He has advanced training in mathematical programming including optimization, advanced multivariate data analysis, and simulation techniques. When he is not teaching or consulting he can be found meditating or heading for an adventurous trek.

Scikit Learn Trainer Ghazaleh Babanejad has received her Ph.D from University Putra Malaysia in Faculty of Computer ‎Science and Information Technology. She is working on recommender systems in the ‎field of skyline queries over Dynamic and Incomplete databases for her PhD thesis. She is also working ‎on Data Science field as a trainer and Data Scientist. She worked on Machine Learning and Process ‎Mining projects. She also has several international certificates in Practical Machine Learning (John ‎Hopkins University) Mining Massive Datasets (Stanford University), Process Mining (Eindhoven ‎University), Hadoop (University of San Diego), MongoDB for DBAs (MongoDB Inc) and some other ‎certificates. She has more than 5 years of experience as a lecturer and database administrator.

Scikit Learn TrainerSyed Muhammad Farrukh Akhtar has more than 15 years of experience analysis, designing, developing, integrating and managing large applications for diverse industries. He has experience working in Dubai, Pakistan, Germany and Malaysia, strong hands-on experience in software design, development and integration on a different platform like IBM J2EE, Oracle and Microsoft.Net, Big data, Hadoop, Spark, HBase, Hive, Sqoop, Flume and NoSQL. He also has expertise in Machine Learning/ Deep Learning with Tensor Flow, Keras and Python, excellent skills in React, Ionic 2, Angular 2, Mobile Apps with React Native and Node.js. He is highly knowledgeable in object-oriented software development, requirements analysis, and database design. Possess deep understanding of Open Source technologies’ applicability in emerging business areas. He possesses excellent knowledge in Rational Unified Process (RUP); Rational Software Architect; data modelling and mapping; and extensible system design using the UML and Visio. Professional experience on J2EE, JMS, Web Sphere, Oracle, Spring, Hibernate, Struts and 3-Tier Web-based Applications Development.

Customer Reviews (7)

Might RecommendReview by Chin Swee Miin
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
For tea break, at least should have coffee e.g. coffee machine for participants. Reminder: Not 3-in-1 instant coffee.

Organizer did not give clear instruction. Thought that lunch is included (Posted on 12/17/2018)
Will RecommendReview by Raymond Ooi Khai Boon
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Include more sample code to understand the concepts of the different algorithms (i.e. expand beyond just the iris and digits datset), and provide more hints/ answers to the challenge questions

The instructor Ghazaleh Babanejad is very knowledgeable in this area of machine learning with Python, and has thorough knowledge in the "why" of how the algorithm works as well as the "how" in the algorithms. Subject to my employer, I hope to take another class under her as she was highly supplementary to my machine learning knowledge with Python. (Posted on 8/1/2018)
Will RecommendReview by NORMALA BINTI CHE EEMBI @ JAMIL
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 3/13/2018)
Might RecommendReview by Jeffery Ng
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
I supposed it should be a 2 day course unless the participants are well versed in Machine Learning theory. Else the theory itself will take the whole day. Perhaps having the Titanic demo earlier will provides a better understanding. (Posted on 10/10/2017)
Will RecommendReview by Teh Kian Wooi
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
With related examples (Posted on 8/3/2017)
Will RecommendReview by Rache Lim
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
too short training duration, require a basic class for modeling understanding before attending the class (Posted on 8/3/2017)
Will recommendReview by stella
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
ensure to improve schedule management (Posted on 7/10/2016)

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