Certificate Course in
Data Analytics For Managers
- 48 Hours Classroom & Online Sessions
- 80+ Hours Assignments & eLearning
- 100% Job Assistance
- 2 Capstone Projects
- Industry Placement Training
- HRDF SBL-KHAS Claimable!
3152 Learners
Academic Partners & International Accreditations
"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
Total Duration
3 Months
Prerequisites
- 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.
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
Who Should Attend
Block Your Time
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
- CRISP-DM
- 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
- Business Understanding
- 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
- Sampling Techniques
- 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
- Univariate
- 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
- ANOVA
- 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
Tools Covered
Data Analytics For Managers Trends in Malaysia
Data Analytics Course in Malaysia has gathered steam and will evolve in the years to come. The advent of Big Data has led to a data explosion of sorts. Big Data Analytics has opened myriad opportunities for students and working professionals. The Data Analytics Course includes an introduction to foundation Data analytics as well as Advanced Data Analytics using Python and R programming. Students who complete this course can command very high salaries in Malaysia and other countries. Python which is the top programming tool and R which is second best allows you to accomplish a lot of routine data analytics tasks with ease.
Malaysia with its peninsular mainland in the South - Eastern part of Asia is rich in Flora & Fauna. It is one of the fastest-growing economies and has embraced emerging technologies from around the globe. Many industries in the federal capital region of Kuala Lumpur are now using advanced Data Analytics for their business operations. Petronas, the leading company in Kuala Lumpur has been using Data Analytics for quite some time. Analytics professionals with knowledge for Python and R are now very much in demand because businesses are obsessed with Data Analytics is driven decision making.
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How We Prepare You
- Additional Assignments of over 60-80 hours
- Live Free Webinars
- Resume and LinkedIn Review Sessions
- 6 Months Access to LMS
- 24/7 Support
- Job Assistance in Data Analytics Fields
- Complimentary Courses
- Unlimited Mock Interview and Quiz Session
- Hands-on Experience in a Live Project
- Life Time Free Access to Industry Webinars
Call us Today!
Data Analytics For Managers Course Panel of Coaches
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.
Bhargavi Kandukuri
- Professional Experience: Over 19+ years in electronics and communications engineering.
- Expertise: Specializes in business analytics, quality management, and data visualization with Tableau.
- Experience: Worked with Infosys Technologies, iGate, Patni Global Solutions as a technology analyst.
- Certifications: Tableau Desktop 10 Qualified Associate.
Sreeja Depuru
- Professional Experience: 10 years in cloud computing and Internet of Things (IoT).
- Expertise: Specializes in data analytics, solution architecture, and IoT.
- Experience: Worked with Innodatatics and 360DigiTMG.
- Certifications: AWS Certified Solutions Architect - Associate.
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 Analytics Certificate is your passport to an accelerated career path.
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Alumni Speak
"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
"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
"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
"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
"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
Our Alumni Work At
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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 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 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 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
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 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
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.
Student Voices
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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