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Data Science Using Python and R Certificate Course

Data Science is the prerequisite for making your data effective. Unravel and unearth new opportunities in Data Science. Learn Statistical Analysis, Machine Learning, Predictive Analytics, and much more.
  • 48 Hours Classroom, Virtual, or Self-paced Sessions
  • 60 Hours Streaming Hours & Coursework
  • 30 Hours Real-Time Industry Projects
  • 100% Job Assistance
  • Blockchain enabled tamper-proof security certificate
  • 100% HRD Corp Claimable!
data science review in malaysia - 360digitmg
411 Reviews
data science review in malaysia - 360digitmg
14673 Learners
Academic Partners & International Accreditations
  • AiSPRY
  • Data Science foundation with SUNY
  • data scientist certification panasonic
  • Data Science foundation with Microsoft
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Calendar-for-Virtual Interactive Classes

Start Date

Data Science Course

data science in malaysia - 360digitmg

Total Duration

3 Months

data science training in malaysia - 360digitmg

Prerequisites

  • Computer Skills
  • Basic Programming Knowledge
  • Analytical Mindset

Data Science Certificate Course Overview

This three-month Data Science certification 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 Training based in Malaysia, they will learn to unleash the power of Python and R to create machine learning and neural network algorithms. This 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 course, 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 Malaysia

 

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 Scientist Certification Malaysia 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.

Learning Outcomes of Data Science Course in Malaysia

In this data-driven environment certification in Data Science course in malaysia 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 programme is one of the most comprehensive course in malaysia 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 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.

 

 

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

data science course - 360digitmg

48 hours

Classroom, Virtual, or Self-paced Sessions

data science course - 360digitmg

60 hours

Streaming Hours & Coursework

data science course duration - 360digitmg

30 hours

Real-Time Industry Projects

Who Should Sign Up?

  • Business Analysts, Data Analyst, Data Scientist, Data Engineer, Project Managers for Data Analytics or Data Stream projects
  • Schools, Universities and Colleges looking to upskill their faculties in Digital Courses
  • Graduates who are looking to build a career in Data Science, Machine Learning, Forecasting, Business Intelligence, etc.
  • Students who are aiming to work in IT industry on emerging technologies

Data Science Courses Modules in Malaysia

This 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.

Get about, CRISP - ML(Q) the perfect Project Management Methodology used for handling Data Mining projects. Understand the entire process flow including Business Problem definition, Data Collection, Data Cleansing, Feature Engineering, Feature Selection, Model Building, Deployment and Maintenance. Get introduced to the principles of big data and learn about the opportunities being created. Understand about how Data is generation and explosion of data, Innovations in the space of analytics. Learn how to distinguish between data types, Exploratory data analysis, the Various moments of Business decisions and various Graphical techniques. Learn about probability and probability distribution namely Z distribution and Student's t-distribution.

Learn about Hypothesis testing, the many Hypothesis testing Statistics, work with the Null Hypothesis & Alternative hypothesis and Types of hypothesis testing. Interpret the results of Hypothesis test and probabilities of Alpha error, understand Type I and Type II errors. Get introduced to Linear regression, various components of Linear regression viz regression line, Linear regression equation, the concept of Ordinary Least Square. Get introduced to Linear regression analysis, and Linear regression examples.

Understand the Linear regression in a multivariate scenario, understand collinearity and how to deal with it. Get introduced to the analysis of Attribute Data, understand the principles of Logistic regression, Binary Logistic regression analysis. Learn about the Multiple Logistic regression, Probability measures, and its interpretation. Get clarity on the confusion matrix and its elements. Get introduced to “Cut off value” estimation using AUC and ROC curve, understand False Positive Rate, False Negative Rate, Sensitivity, Specificity. Gain a birds-eye view to various advanced regression techniques and analysis of count data namely Poisson regression, Negative binomial regression. Learn when to use Poisson regression and negative binomial regression for predicting count data.

Learn about modeling using KNN, the K nearest neighbour algorithm using KNN algorithm examples. The KNN classifier is one of the most popular classifier algorithms. Decision tree & Random forest are one of the most powerful classifier algorithms today. Under this tutorial learn about Decision Tree analysis, Decision Tree examples and Random Forest algorithms. Also learn about the various ensemble machine learning algorithms. Text Mining or Text Data Mining are the most widely used analyzing tools for unstructured data. As part of the session, learn about Text analytics and the various text mining techniques in the text mining application, text mining algorithms, and sentiment analysis. Gain a ‘hands-on’ on how to extract data from Social Media, download user reviews from E-commerce sites and travel sites. Generate various visualizations using the downloaded data.

Under the Naïve Bayes classifier tutorial, learn how the classification modelling is done using Bayesian classification, understand the same using Naïve Bayes example. Learn about Naïve Bayes through the example of text mining. Artificial Neural Network and Support Vector Machines are the 2 powerful Deep learning algorithms. Get introduced to Perceptron Algorithms, Artificial Neural Networks, Multilayer Perceptron (MLP). Learn how to work with Support Vector Machine, SVM classifiers, and SVM regression. Get introduced to Association rules in data mining to decode the relationship between entities, understand how the Apriori algorithm works, and the association rule mining algorithm works.

Description: As part of data mining unsupervised, get introduced to various clustering algorithms, learn about Hierarchical clustering, K-means clustering using clustering examples, know what clustering machine learning is all about. Learn about K-means Clustering, Clustering ratio, and various clustering metrics. Get introduced to methods of making optimum clusters. Learn the need for data reduction in data mining using dimensionality reduction techniques. Learn about the advantages of dimensionality reduction using PCA. Get introduced to the difference between cross-sectional data and Time-series data. Various stages of forecasting projects, components of Time-series, visualization techniques, model-based techniques and learning how to evaluate the forecasting models accuracy.

Self-paced Data Science Course Modules

Extract meaningful information from temporal data, enabling accurate predictions and insights.

  • RNN, Bidirectional RNN, Deep Bidirectional RNN
  • Transformers for Forecasting
  • N-BEATS, N-BEATSx
  • N-HiTS
  • TFT - Temporal Fusion Transformer

Understands and uses advanced models that can generate consistent, contextual information across applications.

  • Sequence 2 Sequence Models
  • Transformers
  • Generative AI
  • ChatGPT
  • DALL-E-2
  • Mid Journey
  • Crayon

Harness the power of well-designed prompts to better interact with language models and unlock their true potential.

  • What Is Prompt Engineering?
  • Understanding Prompts: Inputs, Outputs, and Parameters
  • Crafting Simple Prompts: Techniques and Best Practices
  • Evaluating and Refining Prompts: An Iterative Process
  • Role Prompting and Nested Prompts
  • Chain-of-Thought Prompting
  • Multilingual and Multimodal Prompt Engineering
  • Generating Ideas Using "Chaos Prompting"
  • Using Prompt Compression
Tools Covered
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Course Fee Details

Online Interactive Sessions
Mode of training: Live Online
  • 10+ hours of live online doubt clarification sessions
  • Free access to USD 500 worth study materials - mindmaps, digital book on Data Science & many more
  • Blockchain security enabled tamper-proof certificate(s)
  • Real-life industry-based projects with AiSPRY
  • 100% HRD Corp-claimable courses
  • Free Learning Management System Access

Next Batch: 14th December 2024

MYR 3,900

Minimum instalments cost starting from: MYR 1,404

Learners 15763 Learners

Rating 286 Reviews

Employee Upskilling
Mode of training: Onsite or Live Online
  • Minimum 10 participants per batch for Onsite training
  • Pre & Post Assessment Services
  • Blockchain security enabled tamper-proof certificate(s)
  • Customised Curriculum with industry-relevant use cases
  • 100% HRD Corp-claimable courses
  • Free Learning Management System Access

Next Batch: 14th December 2024

Corporate Group DiscountsUp to 30% for 3 participants & above

Learners 15763 Learners

Rating 286 Reviews

Payment Accepted

Payment Accepted

All prices are applicable with 8% taxes.

Exclusive

Practical Data Analytics: Work-Integrated Learning Course

Dive deep into analytics and transform your career in just 6 months.

Elevate your data insights and seamlessly transition from learning to working.

  • Work-Integrated Learning: Transition from learning to working in 6 Months - 30 days
  • Tackle 3 Industry-specific real-time projects to refine and showcase your skills
  • Secure 100 hours of credible working experience in data analytics
  • HRDC claimable and 6 months instalments available

Offer ends:15th Jan,2025

How we prepare you
  • Additional Assignments of over 60-80 hours
    Additional Assignments of
    over 60-80 hours
  • Live Free Webinars
    Live Free Webinars
  • Resume and LinkedIn Review Sessions
    Resume and
    LinkedIn Review Sessions
  • 6 Months Access to LMS
    6 Months Access to LMS
  • Job Assistance in Data Science Fields
    Job Assistance in
    Data Science Fields
  • Complimentary Courses
    Complimentary Courses
  • Unlimited Mock Interview and Quiz Session
    Unlimited Mock
    Interview and Quiz Session
  • Hands-on Experience in a Live Project
    Hands-on Experience
    in a Live Project
  • Life Time Free Access to Industry Webinars
    Life Time Free Access
    to Industry Webinars

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Data Science Course Panel of Coaches

Data Science Course Training -360digitmg

Bharani Kumar Depuru

  • Professional Experience: Over 18+ years in data analytics, digital transformation, and Industrial Revolution 4.0.
  • Expertise: Specializes in data analytics and digital transformation.
  • Corporate Clients: Worked with Deloitte, HPE, Amazon, Tech Mahindra, Cummins, Accenture, and IBM.
  • Certifications: PMP, PMI-ACP, PMI-RMP, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner.
Read More >
 
Data Science Course Training - 360digitmg

Samson Swaroop Paturi

  • Professional Experience: Over 17+ years in machine learning, AI, and big data/data lake systems.
  • Expertise: Specializes in machine learning, AI, and big data.
  • Experience: Worked with Capgemini, Florida Power & Light Company, ComTec Information Systems, and IBM.
  • Certifications: Certified Scrum Product Owner (CSPO), Six Sigma Green Belt, ITIL Foundation Level, IBM logo Advisory Product Services Professional.
Read More >
 
Data Science Course Training -360digitmg

Adityaveer Dhillon

  • Professional Experience: Over 4+ years in data science and analytics.
  • Expertise: Specializes in GenAI, data science, business analytics, quality management, and AI.
  • Solutions Experience: Team Lead Data Specialist at 360DigiTMG; Data Scientist at AISPRY.
  • Certifications: Python, SQL, Power BI, Data Science, and AI.
Read More >
 
data science certificate in malaysia - 360digitmg

Data Science 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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Alumni Speak

Nur Fatin

"Coming from a psychology background, I was looking for a Data Science certification that can add value to my degree. The 360DigiTMG program has such depth, comprehensiveness, and thoroughness in preparing students that also looks into the applied side of Data Science."

"I'm happy to inform you that after 4 months of enrolling in a Professional Diploma in Full Stack Data Science, I have been offered a position that looks into applied aspects of Data Science and psychology."

Nur Fatin

Associate Data Scientist

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Thanujah Muniandy

"360DigiTMG has an outstanding team of educators; who supported and inspired me throughout my Data Science course. Though I came from a statistical background, they've helped me master the programming skills necessary for a Data Science job. The career services team supported my job search and, I received two excellent job offers. This program pushes you to the next level. It is the most rewarding time and money investment I've made-absolutely worth it.”

Thanujah Muniandy

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Ann Nee, Wong

"360DigiTMG’s Full Stack Data Science programme equips its graduates with the latest skillset and technology in becoming an industry-ready Data Scientist. Thanks to this programme, I have made a successful transition from a non-IT background into a career in Data Science and Analytics. For those who are still considering, be bold and take the first step into a domain that is filled with growth and opportunities.”

Ann Nee, Wong

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Mohd Basri

"360DigiTMG is such a great place to enhance IR 4.0 related skills. The best instructor, online study platform with keen attention to all the details. As a non-IT background student, I am happy to have a helpful team to assist me through the course until I have completed it.”

Mohd Basri

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Ashner Novilla

"I think the Full Stack Data Science Course overall was great. It helped me formalize and think more deeply about ways to tackle the projects from a Data Science perspective. Also, I was remarkably impressed with the instructors, specifically their ability to make complicated concepts seem very simple."

"The instructors from 360DigiTMG were great and it showed how they engaged with all the students even in a virtual setting. Additionally, all of them are willing to help students even if they are falling behind. Overall, a great class with great instructors. I will recommend this to upcoming deal professionals going forward.”

Ashner Novilla

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Our Alumni Work At

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FAQs for Data Science Certification Course

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 AiSPRY, 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 data science training, 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 Certification of Data Science.

The data science courses in Malaysia typically span 3 months, with 48 hours of classroom, virtual, or self-paced sessions. This is complemented by 60 hours of streaming hours and coursework, and 30 hours dedicated to real-time industry projects.

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, certification costs are typically covered in the course fees for this program, including examination fees. The data scientist certification Malaysia is awarded upon successful completion of course requirements, with no additional charges.

Yes, data science is in high demand in Malaysia. Various industries, such as finance, technology, and healthcare, increasingly require data-driven decision-making. This trend drives the demand for skilled data scientists to analyse complex data and provide actionable insights.

Data Scientist salaries in Malaysia typically vary from RM 4,000 to RM 15,000 per month for entry-level roles. Mid-level data scientists can expect to earn between RM 8,000 and RM 20,000 per month, while seasoned professionals with several years of experience and skill can command monthly wages ranging from RM 15,000 to RM 35,000 or higher.

To become a data scientist in Malaysia, first earn a degree in a relevant discipline, such as computer science, statistics, or mathematics. Enroll in a data science course in Kuala Lumpur to master key skills in programming languages like Python and R, data analysis, machine learning, and statistical modeling. Completing internships or projects will help you gain practical experience, and staying updated on industry trends is crucial. Networking with professionals can also offer valuable insights and opportunities in the field.

Jobs in field of Data Science in malaysia

Jobs in Field of Data Science in Malaysia

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 Malaysia for Data Scientist

Salaries in Malaysia 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 Malaysia

Data Science Projects in Malaysia

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 Data Science

Role of Open Source Tools in Data Science

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 Malaysia 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.

Companies That Trust Us

360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.

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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

Data Science Certification Course Training in Other Locations - Data Science Training in Malaysia, Data Science Training in Malaysia, Data Science Certification in Malaysia, Data Science Institute in Malaysia, Data Science in Kuala Lumpur, Data Science in Penang, Data Science in Johor, Data Science Malaysia, Data Scientist Malaysia, Data Scientist Course Malaysia, Data Science is a way of communicating insightful information that is hiding under mountains of data. Data science is the voice for numbers to spill out valuable information that is vital and meets the empirical demands of businesses today.

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