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Data Science Using Python & R

Become a Data Scientist and learn Statistical Analysis, Machine learning, Predictive Analytics many more.
  • 48 Hours Classroom & Online Sessions
  • 80+ Hours Assignments & eLearning
  • 100% Job Assurance
  • 2 Capstone Projects
  • Industry Placement Training
  • HRDF SBL-KHAS Claimable!
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The demand for Data Scientists to grow exponentially in the Asia-Pacific region. The Philippines will need 340,890 data scientists and Malaysia 21,000 by the year 2022. - (Source). Malaysia has emerged as a thriving ecosystem for learning opportunities in the field of Data Science with the Malaysian MDEC ( Multimedia Development Corporation) having assigned seven public and private institutes of higher learning to offer data science courses. A survey of the Malaysian industry revealed a 25 % growth in demand for professionals with skills in Big Data, Data Analytics, and Web Development. The five most sought after digital skills are Big Data, software and user testing, Mobile Development, Cloud Computing, and software engineering management.

Data Science

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Total Duration

3 Months

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Prerequisites

  • Computer Skills
  • Basic Programming Knowledge
  • Analytical Mindset

Data Science Certification Programme Overview

This three-month Data Science certification course with Python and R programming will empower students with skills in Data Analytics, Data Mining, Machine Learning, Predictive Modelling, and Regression Analysis. In this Data Science course based in Penang, they will learn to unleash the power of Python and R to create machine learning and neural network algorithms. This Data Science training course aims to serve the learning needs of IT professionals and college students gearing to make the transition to data science. The student will appreciate descriptive and predictive analytics and learn to analyze structured and unstructured data with various tools and techniques like Data Preparation, Data Cleansing, Exploratory Data Analysis, Feature Engineering, Feature Extraction, Feature Selection, and Text Mining. At the end of this best Data Science course in Malaysia, they will build prediction models for daily operability. They can also master Black box techniques, Neural Network programming, and Data Visualization methods. Propel yourselves to great heights in your Data Science career with the aid of this program from the best Data Science training institute from Penang.

What is Data Science? Data science is an amalgam of methods derived from statistics, data analysis, and machine learning that are trained to extract and analyze huge volumes of structured and unstructured data.

Who is a Data Scientist? A Data Scientist is a researcher who has to prepare huge volumes of big data for analysis, build complex quantitative algorithms to organize and synthesize the information, and present the findings with compelling visualizations to senior management.

A Data Scientist enhances business decision making by introducing greater speed and better direction to the entire process.

A Data Scientist must be a person who loves playing with numbers and figures. A strong analytical mindset coupled with strong industrial knowledge is the skill set most desired in a Data Scientist. He must possess above the average communication skills and must be adept in communicating the technical concepts to non - technical people.

Data Scientists need a strong foundation in Statistics, Mathematics, Linear Algebra, Computer Programming, Data Warehousing, Mining, and modeling to build winning algorithms.

They must be proficient in tools such as Python, R, R Studio, Hadoop, MapReduce, Apache Spark, Apache Pig, Java, NoSQL database, Cloud Computing, Tableau, and SAS.

Course Details

Data Science Course Outcomes in Penang

In this data-driven environment a certification in Data Science prepares you for the surging demand of Big Data skills and technology in all the leading industries.There is a huge career prospect available in the field of data science and this Data Science Certification Programme is one of the most comprehensive Data Science courses in the industry today.This training will equip the students with logical and relevant programming abilities to build database models. The students will explore the various stages of the Data Science Lifecycle in the trajectory of this Data Science course. Initially conceptualize Data preparation, Data Cleansing, Exploratory Data Analysis, and Data Mining( Supervised and Unsupervised). Progressively learn the theory behind Feature Engineering, Feature Extraction, and Feature Selection. Perform Predictive modeling using regression analysis. Build machine learning, Deep Learning, and Neural Network algorithms with Python and R language. Apprehend forecasting to take proactive business decisions. Script algorithms for neural networks, time series analysis and forecasting in this Data Science Course in Penang.

Work with various data generation sources
Perform Text Mining to generate customer Sentiment analysis
Analyse Structured and Unstructured data using different tools and techniques
Develop an understanding of Descriptive and Predictive Analytics
Apply data-driven, Machine Learning approaches for business decisions
Build prediction models for day-to-day applicability
Perform forecasting to take proactive business decisions
Use Data Visualisation concepts to represent data for easy understanding
Block Your Time
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48 hours

Classroom Sessions

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80+ hours

Assignments &
e-Learning

data science course duration in Penang - 360digitmg

80+ hours

Live Projects

Who Should Sign Up?
  • IT Engineers
  • Data and Analytics Manager
  • Business Analysts
  • Data Engineers
  • Banking and Finance Analysts
  • Marketing Managers
  • Supply Chain Professionals
  • HR Managers

Data Science Training Modules in Penang

This Data Science course begins with an introduction to Statistics, Probability, Python and R programming, And Exploratory Data Analysis. Participants learn to perform Data Mining Supervised with Linear regression and Predictive Modelling with Multiple Linear Regression techniques. Data Mining Unsupervised using Clustering, dimension reduction, and association rules is also dealt with in detail. A module is dedicated to scripting machine learning algorithms and enabling Deep Learning and Neural Networks with Black Box techniques and SVM. Learn to perform proactive forecasting and time series analysis with algorithms scripted in Python and R.

Understand various data sources and why organizations are gearing up to store the data like never before. Learn on what are the various applications of data science in various industries ranging from FSI to LSHC to Retail and many more. Also one will appreciate the job opportunities in the space of data science, data modeling, and data analysis. Finally understand the golden rule on how to become a successful data scientist, data modeler, data analyst, etc.

Learn about the Project Management Methodology, CRISP-DM, for handling Data Science projects & various concepts used in defining business problems and then performing data collection in line with business problems. Understand the importance of documenting the business objectives & business constraints so that the entire project is performed to solve business problems. Project charter overview will help participants understand the real-world documentation aspect as well.

Learn about data preparation and data cleansing in data science projects to ensure that appropriate data is provided to the next step. Outlier analysis or treatment, handling missing values using imputation, transformation, normalization/standardization, etc., will be explained in thorough detail. Understand the various moments of a business decision and graphical representation so that structured descriptive analytics or descriptive statistics is performed. This exploratory data analytics is the first step in data analytics to draw meaningful insights.

Learn about applying domain knowledge to the data so that more meaningful variables are derived. Understand two main modules of feature engineering including feature extraction and feature selection. Knowing how to shortlist the critical inputs from trivial many inputs is the key to ensuring the high performance of the machine learning models. Understand about extracting features from structured as well as unstructured data such as videos, images, audio, textual files, etc.

Understand one of the key inferential statistical techniques called Hypothesis testing. Understand various parametric hypothesis tests. Learn about the implementation of a Regression method based on the business problems to be solved. Understand about Linear Regression as well as Logistic Regression techniques used to handle continuous as well as discrete output prediction. Evaluation techniques by understanding the measure of Error (RMSE), problems while building a Regression Model like Collinearity, Heteroscedasticity, overfitting, and Underfitting are explained in detail.

Understand the advanced regression models such as Poisson Regression, Negative Binomial Regression, Zero-Inflated models, etc., used to predict the count output variables. Learn about the various scenarios which trigger the application of advanced regression techniques. Understanding and evaluating the models using appropriate performance and accuracy measures of regression are explained in detail.

Data Mining branch called unsupervised learning is extremely important in solving problems, which require the application of only unsupervised learning tasks and also used to support predictive modeling. Clustering or segmentation has two prime techniques – K-Means clustering, as well as Hierarchical clustering and both, are explained in finer detail. Alongside, participants will also learn about handling datasets with large variables using dimension reduction techniques such as Principal Component Analysis or PCA. Finally one will learn about Association rules also called affinity analysis or market basket analysis or relationship mining.

The majority of unstructured data is in textual format and analyzing such data requires special techniques such as text mining or also called as text analytics. Techniques such as DTM/TDM using Term Frequency, Inverse Document Frequency, etc. are explained in this module. One will also learn about generating a word cloud, performing sentiment analysis, etc. Also, advanced Natural Language Processing techniques such as LDA, topic mining, etc., are explained using practical use cases. Also, the learning includes extracting unstructured data from social media as well as varied websites.

A major branch of study in data science is Machine Learning also called Data Mining Supervised Learning or Predictive Modelling. One will learn about K Nearest Neighbors (KNN), Decision Tree (Boosting), Random Forest (Bagging), Stacking, Ensemble models and Naïve Bayes. One will learn about the various regularization techniques as well as understand how to evaluate for overfitting (variance) and underfitting (bias). All these are explained using industry relevant use cases and mini-projects.

Black box machine learning algorithms are extremely important in the field of machine learning. While there is no interpretation in the models, accuracy is unmatched in comparison to other shallow machine learning algorithms. Learn about the Perceptron algorithm and Multi-layered Perceptron algorithm or MLP. Understand about Kernel tricks used within Support Vector Machine algorithms. Understand about linearly separable boundaries as well as non-linear boundaries and now to solve these using Deep learning algorithms.

Understand the difference between cross-sectional data versus time series data. Search about the forecasting strategy employed in solving business problems. Understand various forecasting components such as Level, Trend, Seasonality & Noise. Also, learn about various error functions and which one is the best given a business scenario. Finally, build various forecasting models ranging from linear to exponential to additive seasonality to multiplicative seasonality.

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How we prepare you
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    Additional assignments of over 60-80 hours
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    Live Free Webinars
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    Resume and LinkedIn Review Sessions
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    3 Month Access to LMS
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    24/7 support
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    Job assistance in Data Science fields
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Data Scientist Course Panel of Coaches in Penang

bharani kumar - 360digitmg

Bharani Kumar Depuru

  • Areas of expertise: Data analytics, Digital Transformation, Industrial Revolution 4.0
  • Over 14+ years of professional experience
  • Trained over 2,500 professionals from eight countries
  • Corporate clients include Hewlett Packard Enterprise, Computer Science Corporation, Akamai, IBS Software, Litmus7, Personiv, Ebreeze, Alshaya, Synchrony Financials, Deloitte
  • Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, AgilePM (DSDM Atern)
  • Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business
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sharath - data science trainer - 360digitmg

Sharat Chandra Kumar

  • Areas of expertise: Data sciences, Machine learning, Business intelligence and Data visualisation
  • Trained over 1,500 professional across 12 countries
  • Worked as a Data scientist for 14+ years across several industry domains
  • Professional certifications: Lean Six Sigma Green and Black Belt, Information Technology Infrastructure Library
  • Experienced in Big Data Hadoop, Spark, NoSQL, NewSQL, MongoDB, R, RStudio, Python, Tableau, Cognos
  • Corporate clients include DuPont, All-Scripts, Girnarsoft (College-dekho, Car-dekho) and many more
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data science trainer - Nithin - 360digitmg

Nitin Mishra

  • Areas of expertise: Data sciences, Machine learning, Business intelligence and Data visualisation
  • Over 20+ years of industry experience in data science and business intelligence
  • Trained professionals from Fortune 500 companies and students at prestigious colleges
  • Experienced in Cognos, Tableau, Big Data, NoSQL, NewSQL
  • Corporate clients include Time Inc., Hewlett Packard Enterprise, Dell, Metric Fox (Champions Group), TCS and many more
Read More >
 
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Certificate

Earn a certificate and demonstrate your commitment to the profession. Use it to distinguish yourself in the job market, get recognised at the workplace and boost your confidence. The Data Science Certificate is your passport to an accelerated career path.

**All certificate images are for illustrative purposes only. The actual certificate may be subject to change at the discretion of the Certification Body.

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FAQs for Data Science Bootcamp in Penang

Different organisations use different terms for Data Professionals. You will sometimes find these terms being used interchangeably. Though there are no hard rules that distinguish one from another, you should get the role descriptions clarified before you join an organisation.

With growing demand, there is a scarcity of Data Science/Business Analytics professionals in the market. If you can demonstrate strong knowledge of Data Science concepts and algorithms, then there is a high chance for you to be able to make a career in this profession.

 

360DigiTMG provides internship opportunities through Innodatatics, our USA-based consulting partner, for deserving participants to help them gain real-life experience. This greatly helps students to bridge the gap between theory and practical.

There are plenty of jobs available for Data Professionals. Once you complete the training, assignments and the live projects, we will send your resume to the organisations with whom we have formal agreements on job placements.

 

We also conduct webinars to help you with your resume and job interviews. We cover all aspects of post-training activities that are required to get a successful placement.

While there are a number of roles pertaining to Data Professionals, most of the responsibilities overlap. However, the following are some basic job descriptions for each of these roles.

 

As a Data Analyst, you will be dealing with Data Cleansing, Exploratory Data Analysis and Data Visualisation, among other functions. The functions pertain more to the use and analysis of historical data for understanding the current state.

As a Data Scientist, you will be building algorithms to solve business problems using statistical tools such as Python, R, SAS, STATA, Matlab, Minitab, KNIME, Weka etc. A Data Scientist also performs predictive modelling to facilitate proactive decision-making.

A data engineer primarily does programming using Spark, Python, R etc. It often compliments the role of a Data Scientist.

A Data Architect has a much broader role that involves establishing the hardware and software infrastructure needed for an organisation to perform Data Analysis. They help in selecting the right Database, Servers, Network Architecture, GPUs, Cores, Memory, Hard disk etc.

After you have completed the classroom sessions, you will receive assignments through the online Learning Management System that you can access at your convenience. You will need to complete the assignments in order to obtain your Data Scientist certificate.

In this blended programme, you will be attending 48 hours of classroom sessions over six days on campus in Kuala Lumpur, Malaysia. After completion, you will have access to the online Learning Management System for another three months for recorded videos and assignments. The total duration of assignments to be completed online is 40-60 hours. Besides this, you will be working on a live project for a month.

If you miss a class, we will arrange for a recording of the session. You can then access it through the online Learning Management System.

We assign mentors to each student in this programme. Additionally, during the mentorship session, if the mentor feels that you require additional assistance, you may be referred to another mentor or trainer.

No, the cost of the certificate is included in the programme package.

Jobs in field of Data Science in Penang
Jobs in field of Data Science in Penang

It is estimated that by the end of 2020 there will be a need for 2000 data scientists and 20000 data professionals. The three main job roles that a student can specialize in are a) Data Scientist, b) Data Analyst, c) Data Engineer.

Salaries in Penang for Data Scientist

Salaries in Penang for Data Scientist

A fresher Data Scientist in an entry-level job can expect a pay of RM 4500-8500. The maximum that an experienced professional can demand is RM 15000. An average software engineer will earn about RM 8000.

Data Science Projects in Penang

Data Science Projects in Penang

The Malaysian Government has placed the digital transformation of Malaysian government systems and corporate offices on priority. It has invited all multinationals to frame a Big Data Policy for the country. The country has progressed so much in digital transformation that it wishes to appoint a Chief Data Scientist over the next few years.

Role of Open Source Tools in Analytics

Role of Open Source Tools in Analytics

Python is easy to learn and maintain and therefore a Godsend to developers in Data Science. Its extended library makes it possible to stretch the applications of Python from Big Data Analytics to Machine Learning. R is the preferred tool of statisticians that enables effective data storage.

Modes of training for Data Science with Python

Modes of training for Data Science with Python

The course in Penang is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of both classroom and online learning. We also support e-learning as part of our curriculum.

Industry Application of Data Science

Industry Application of Data Science

The industries where data science is used in Malaysia are Financial Services. Telecommunications, Information Technology, Education, and Healthcare. The various applications are Data warehousing solutions, Predictive Maintenance, Fraud Detection, Click stream Analytics, and Customer and Social Analytics.

360DigiTMG - Data Science, IR 4.0, AI, Machine Learning Training in Malaysia

Level 16, 1 Sentral, Jalan Stesen Sentral 5, Kuala Lumpur Sentral, 50470 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

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