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Data Analytics For Managers

Data Analytics course empowers you with all the needed skills and trends to lead the changing world. Showcase your Data Analytics skills and make yourself hireable by the top employers.
  • 48 Hours Classroom & Online Sessions
  • 80+ Hours Assignments & eLearning
  • 100% Job Assistance
  • 2 Capstone Projects
  • Industry Placement Training
  • HRDF SBL-KHAS Claimable!
data analytics course review in malaysia - 360digitmg
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"The Data Analytics course has been designed for Managers, Senior Executors, and Decision Makers with an aptitude for analyzing the business data to take advantage while making appropriate decisions. The course details the aspects of Analytics like Statistical Analysis, Explainable Machine Learning Algorithms, the black box model Neural Network, and its architectures. Finally, the program enlightens and encourages the adoption of Analytics for Data-Driven Decision Making.

Data Analytics

data analytics course duration - 360digitmg

Total Duration

3 Months

data analytics course pre-requisite - 360digitmg


  • Computer Skills
  • Basic Mathematical Concepts
  • Analytical Mindset

Data Analytics For Managers Course Overview

This certificate program on Data Analytics Course provides an overview of how Python and R programming can be employed in Data Mining of structured (RDBMS) and unstructured (big data) data. Comprehend the concepts of Data Preparation, Data Cleansing, and Exploratory Data Analysis. Perform Text Mining to enable Customer Sentiment Analysis. Learn Machine learning and developing Machine Learning Algorithms for predictive modeling using Regression Analysis. Assimilate various black-box techniques like Neural Networks, SVM, and present your findings with attractive data visualization techniques. By Data Analytics course in Malaysia, students will be empowered with skills in Data Analytics, Data Mining, Machine Learning, Predictive Modelling, and Regression Analysis in addition to programming languages Python, R and Tableau.

What is Data Analytics?

Data Analytics is the process of delivering valuable insights from data through quantitative and qualitative approaches. The process consists of extracting data and categorising it into various forms, to make it resourceful and valuable. At present many Data Analytics techniques use software combined with Machine Learning algorithms, Artificial Intelligence, and other specific features.

The various types of Data Analytics are Prescriptive Analytics, Predictive Analytics, Diagnostic Analytics, and Descriptive Analytics. Every organisation is getting morphed to a data-driven industry. It has to depend on categorising and analysing data for making productive decisions. Globally in many companies, Data Analytics is used to deliver operational efficiencies and unprecedented opportunities.

What is Data Analyst?

A Data Analyst has to explore or fetch data from various sources and design it to maintain resourceful databases and data systems. Data visualization, Data mining, Data cleaning are part of the roles of Data Analyst. A skilled Data Analyst should have statistical and domain knowledge. There are other roles of Data Analyst in various fields such as Marketing Analyst, Operation Analyst, Financial Analyst, Digital Analyst, etc. There is substantial demand for Data Analysts but there is a lack of supply. There is a huge requirement of skilled Data Analysts and people who love analytics can undoubtedly opt for this career. Apart from the lucrative income, there are excellent perks and a lot of liberties. In every sector Data Analysts are necessary to analyze data, they are not limited to specific terrain.

Data Analytics For Managers Course Outcomes in Malaysia

Understand the Impact of Analytics in the Industry
Understand the Applications of Data Analytics
Understand the Project Management Methodology used for Analytics related projects
Learn to deal with various types of Data
Be introduced to Predictive Analytics and distinguish it from Descriptive Analytics
Understand the approach to handle unstructured data

Who Should Attend

Head of Information Technology and Decision-makers
Analytics Managers/Professionals, Business Analysts, Software Developers
Professionals who are looking to get an understanding of Data Analytics, Data Storage, and Data Processing
Finally – Management who are aiming to get an understanding to embark on the journey of Data Analytics

Block Your Time

data analytics course in malaysia - 360digitmg

48 hours

Classroom Sessions

data analytics training in malaysia - 360digitmg

80 hours

Assignments &

data analytics courses

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
  • Math, Science and Commerce Graduates

Data Analytics For Managers Course Modules in Malaysia

By Data Analytics course in Malaysia, students will be exposed to the application of Data Analytics tools in various projects. Understand the finer concepts of predictive analysis and descriptive analysis. Students will be able to perform Data cleansing, categorization of data to devise better strategies. As part of this module, students will get adequate training on Python, R languages, and its applications to solve business problems. Evaluation techniques are explained by calculating the measure of Error (RMSE). Regression Models like Collinearity, Heteroscedasticity, Overfitting, and Underfitting will be explained. As part of this module, the difference between a Time series data and Cross-sectional data is explained. Forecasting techniques explain the response variables variations based on time. Get introduced to the time series components, and the various visualization techniques to interpret the components. Understand the different types of Forecasting techniques available to churn the data. And many other important concepts are explained in the Data Analysis course in Malaysia. Students will be exposed to Black box techniques, Neural Network processing, and Data visualization process.

  • Introduction to Big Data
  • Data, Data, Data everywhere
  • Data and its uses – a case study (Grocery store)
  • Interactive marketing using data & IoT – A case study
  • Stages of Analytics
    • Descriptive Analytics
    • Diagnostic Analytics
    • Predictive Analytics
    • Prescriptive Analytics
  • Machine Learning Categories
    • Supervised Learning
    • Unsupervised Learning
    • Reinforcement Learning
  • Data Science Project Lifecycle
  • Frameworks for Building Machine Learning Systems
    • Knowledge Discovery Databases (KDD)
    • SEMMA (Sample, Explore, Modify, Model, Assess)
    • Cross-Industry Standard Process for Data Mining
    • KDD vs. CRISP-DM vs. SEMMA
    • Business Understanding
      • Define Business Problem – Objective and Constraints
      • Assess and Analyze Scenarios
      • Define Data Mining Problem
      • Project Plan
    • Data Understanding
      • Data Collection
      • Data Description
      • Exploratory Data Analysis
      • Data Quality Analysis
    • Data Preparation
      • Data Integration
      • Data Wrangling
      • Feature Extraction and Engineering
      • Attribute Generation and Selection
    • Modeling
      • Selecting Modeling Methods
      • Model Training
      • Model Evaluation and Improving by Tuning
      • Model Assessment
    • Evaluation
      • Data Partition
      • Evaluate on Training Data
      • Evaluate on Validation Data
      • Evaluate on Test Data
    • Deployment
  • Data Collection
    • Primary Sources
    • Surveys
    • Simulations
    • Sensors Data
    • Design of Experiments, etc
    • Secondary Sources
    • Data Warehouses
    • Data Lakes
    • Databases (SQL, NoSQL, etc.)
  • Data and Datasets
    • Structured Data vs. Unstructured Data
    • Big Data vs. Regular Size Data
    • Cross-Sectional Data vs. Time Series Data
    • Balanced vs. Imbalanced Data
    • Offline vs. Real-Time Data
  • Population and Sample
    • Sampling Techniques
      • Probability Sampling (Unbiased)
      • Non-Probability Sampling (Biased)
    • Sampling Techniques for Handling Balanced vs. Imbalanced Datasets
      • Random Resampling - Under & Over Sampling
      • K-fold Cross-Validation
      • SMOTE - Synthetic Minority Oversampling Technique
      • MSMOTE - Modified SMOTE
      • Cluster-Based Sampling
    • Inferential Statistics
    • Sampling Variation
    • Central Limit Theorem
    • Confidence Interval - Concept
    • Confidence Interval with Sigma
    • t-Distribution/Student's-t Distribution
    • Confidence Interval without Sigma
      • Population Parameter Standard Deviation Known
      • Population Parameter Standard Deviation Not Known
  • Various Graphical Techniques to Understand Data
    • Univariate
      • Line Charts
      • Bar Plots
      • Dot Charts
      • Histograms/Frequency Distribution
      • Box Plots/Box and Whisker Plots
      • Density Plots
      • Q-Q Plots/Normal Quantile – Quantile Plots
    • Bivariate
      • Scatter Plots
  • Business Understanding
  • Formulating a Hypothesis Statements
  • (Ho) Null Hypothesis – Default Condition/Current Condition/Status Quo
  • (Ha/H1) Alternative Hypothesis – Action Condition
  • Type I – (Alpha) – Caused by Rejection of a True Ho
  • Type II Errors – Caused by Not Rejecting a False Ho
  • Hypothesis Test Cases
  • 1 Sample z-test
  • 2 Proportion Tests
  • Introduction to Predictive Analytics
  • Correlation and Causation
  • Measure of Correlation
  • Model Evaluation
  • Decision Tree – Pros and Cons
  • Introduction to Neural Network
  • Introduction to Deep Learning Techniques
  • Data Mining Process
  • Supervised vs Unsupervised Learning
  • Introduction to Hierarchical Clustering / Agglomerative Clustering
  • Introduction Non-Hierarchical Clustering / K-Means Clustering
  • Association Rules - Market Basket / Affinity Analysis / Relationship Mining
  • Recommendation Engine
  • Introduction to Time Series Data
  • Model-Based approaches
  • Smoothing Techniques
    • Moving Average
    • Exponential Smoothing
    • Holts / Double Exponential Smoothing
    • Winters / Holt-Winters
  • AutoML Methods
  • AutoML Systems
  • AutoML on Cloud

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data analytics course in malaysia
data analytics course in malaysia
How We Prepare You
  • Data Analytics course in malaysia
    Additional Assignments of over 60-80 hours
  • Data Analytics course in malaysia
    Live Free Webinars
  • Data Analytics course in malaysia
    Resume and LinkedIn Review Sessions
  • Data Analytics course in malaysia
    6 Months Access to LMS
  • Data Analytics course in malaysia
    24/7 Support
  • Data Analytics course in malaysia
    Job Assistance in Data Analytics Fields
  • Data Analytics course in malaysia
    Complimentary Courses
  • Data Analytics course in malaysia
    Unlimited Mock Interview and Quiz Session
  • Data Analytics course in malaysia
    Hands-on Experience in a Live Project
  • Data Analytics course in malaysia
    Life Time Free Access to Industry Webinars

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Data Analytics For Managers Course Panel of Coaches

Artificial Intelligence & Deep Learning Course Training -360digitmg

Bharani Kumar Depuru

  • Areas of expertise: Data analytics, Digital Transformation, Industrial Revolution 4.0
  • Over 18+ years of professional experience
  • Trained over 2,500 professionals from eight countries
  • Corporate clients include Deloitte, Hewlett Packard Enterprise, Amazon, Tech Mahindra, Cummins, Accenture, IBM
  • Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, (DSDM Atern)
  • Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business
Read More >
Artificial Intelligence & Deep Learning Course Training -360digitmg

Sharat Chandra Kumar

  • Areas of expertise: Data sciences, Machine learning, Business intelligence and Data
  • Trained over 1,500 professional across 12 countries
  • Worked as a Data scientist for 18+ 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, Python, Tableau, Cognos
  • Corporate clients include DuPont, All-Scripts, Girnarsoft (College-, Car-) and many more
Read More >
Artificial Intelligence & Deep Learning Course Training - 360digitmg

Bhargavi Kandukuri

  • Areas of expertise: Business analytics, Quality management, Data visualisation with Tableau, COBOL, CICS, DB2 and JCL
  • Electronics and communications engineer with over 19+ years of industry experience
  • Senior Tableau developer, with experience in analytics solutions development in domains such as retail, clinical and manufacturing
  • Trained over 750+ professionals across the globe in three years
  • Worked with Infosys Technologies, iGate, Patni Global Solutions as technology analyst
Read More >
data analytics course certification - 360digitmg


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 Analytics 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

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

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

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

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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FAQs for Data Analytics For Managers Courses

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.

After you have completed the data science course 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 data analytics course 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.

With growing demand, there is a scarcity of Data Science professionals in the market. If you can demonstrate strong knowledge of Data Science concepts and algorithms, then there is a good chance that you can carve a successful career in this domain.


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 practice.

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. Machine learning algorithms are used to build predictive models using Regression Analysis. A Data Scientist has to develop expertise in Neural Networks and Feature Engineering.


A Data Engineer primarily does programming using Spark, Python, R etc. It often complements 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.

There are plenty of jobs available for Data Professionals. Once you complete the training, assignments and the live projects you can enroll for placement assistance. We help our students in resume preparation. Once the resume is ready we will float it 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. After placement, we provide technical assistance for the first project on the job.

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 Analytics in malaysia

Jobs in the Field of Data Analytics Course in Malaysia

As Malaysia is emerging with many industries, the need for Data Analysts is high. The different job roles in Malaysia are Data Analyst, Data Engineer, Operations Analyst, Marketing Analyst, Financial Analyst, Digital Analyst, and so on.

Salaries in Malaysia for Data Scientist

Salaries for Data Analytics In Malaysia

In Malaysia, the average salary for a Data Analyst is RM 3,791. A fresher Data Analyst in an entry-level job can expect a pay of RM 2500-4500. The senior Data Analyst can expect pay in the range between RM 41k - RM 129k.

Data Analytics Projects in Malaysia

Data Analytics Course Projects in Malaysia

Big Data Analytics Digital government Lab was launched in Malaysia in 2015. So, expertise in Data Analytics is required to work for the following sectors: Agriculture, Finance, Health care, Biodiversity, Logistics, Legal, and many more. Data Analytics will become an essential feature for the industries and organizations to gain a competitive edge.

Role of Open Source Tools in Analytics

Role of Open Source Tools in Analytics

Python is the core tool to learn Data Analytics, Data Science, and for other courses. It is easy to understand and apply for analyzing data. Along with Python, knowledge of R and Tableau is also essential to be professional in Data Analytics.

Modes of training for Data Analytics with Python

Modes of Training for Data Analytics Course

The data analytics course in Malaysia is designed to suit the needs of students as well as working professionals. 360DigiTMG Data Analytics Course offers students the option of both classroom and online learning. We also support e-learning as part of our curriculum. Individual attention is guaranteed to the participants.

Industry Application of Data Analytics

Industry Application of Data Analytics

Data Analytics professionals in Malaysia are required for various streams of industries like Traffic and Transportation Management, Environmental monitoring, Financial Services. Telecommunications, Information Technology, Banks, Manufacturing, Education, and Healthcare.

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

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