Top 4 Data Analytics Courses In Thailand With Live Training
In contemporary business settings, data analytics is a highly lucrative and significant professional skill. As technology covers every sector of the economy, it generates massive amounts of data that can be processed for valuable insights. The data technology sector has expanded in recent years in response to the steady increase in data analytics expertise. If you’re inquisitive about a data analytics course to pursue a career in the field and need some direction in finding an institution to pursue the course of study, this read will help you to provide significant information. Let’s take a quick look at this article Data Analytics Courses In Thailand.
The term “data analytics” is used to refer to the collection, organization, analysis, and interpretation of data to make better decisions. Data analysis, once the exclusive province of behemoths like Facebook and Google, is now within the reach of practically anybody.
Budget and sales numbers, as well as more complex data systems like a massive enterprise data warehouse, are all readily available to businesses of all sizes. In addition, even small businesses can potentially collect more data by doing things like making their website more user-friendly or making use of the analytics features included in their preferred social media sites.
The sheer volume of digital data now at our disposal has made it possible to make discoveries that were just not possible even a few short years ago. However, we can’t learn much from raw data on its own. Data requires analysis before it can provide useful insights.
Use of Tools in Data Analytics
Data analysts utilize a wide variety of programs to gather and examine information, and then to present findings in a way that can be understood by those who are not trained in data analysis. Some of the most common resources used by Data Analysts are:
One of the more commonly used statistical tools among Data Analysts is Microsoft Excel. Sixty-six per cent of data professionals selected it as their most used tool in the latest Digital Skills Survey, down from eighty-one per cent in the previous year. The decline in Excel users could be attributable to several factors, such as the vulnerability of spreadsheet data to unintentional loss and the impossibility of real-time data and information sharing.
Data analysts rely on SQL almost as much as they rely on Excel. Learning SQL, the de facto standard query language for management of databases, should be a top focus for prospective Data Analysts, as it is utilized frequently by 48% of respondents.
Python Instructions Data Analysts should be fluent in Python because it is the industry standard for statistical programming. R, another significant programming language for data analytics, is utilized by 15% of Data Analyst respondents, but 45% of Data Analysts say they often use the Python big-data number cruncher.
Spark is the most popular analytical framework, with 43% of experts choosing it as their preferred structure for writing solutions across a variety of operators for large-scale data processing; Hadoop comes in at a close second with 24%.
Nearly two-thirds of all Data Analysts use some form of data visualization software, with Tableau being the most popular. Additionally, the Matplotlib and ggplot2 visualization programs for Python and R are widely used.
Competence in a programming language is required for data analysis, and Python and ‘R’ are two popular options. It would be challenging for an individual to analyze and process large datasets in a way that calculates meaningful insights in the absence of coding expertise.
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Top 4 Data Analytics Courses in Thailand
1. IIM SKILLS
IIM SKILLS is a student-oriented and internationally recognized online educational platform that offers professional programs for learners including data analytics courses in Thailand. The Data Analytics Course is a carefully developed curriculum that corresponds to each student’s specific requirements and helps them lay the foundation for further study.
- Course Name – Data Analytics Master Course
- Course Fee – 21310.93 Thai Baht
- Duration – 6 Months Of Live Training + 3 Months Of Internship
|Module Name||Important Topic|
Module 1: Basic and Advanced Excel
|Introduction to Data Handling|
|Data Manipulation Using Functions|
|Data Analysis and Reporting|
|Data Visualization in Excel|
|Overview of Dashboards|
Module 2: Visual Basic Application
|How VBA Works with Excel|
|Key Components of Programming Language|
|Programming Constructs in VBA|
|Functions & Procedures in VBA|
|Objects & Memory Management in VBA|
|Controlling the Accessibility of Your Code|
|Communicating with Your Users|
Module 3: SQL
|Basics RDBMS Concepts|
|Utilizing the Object Explorer|
|Data Based Objects Creation (DDL Commands)|
|Data Manipulation (DML Commands)|
|Accessing Data from Multiple Tables Using SELECT|
|Optimizing Your Work|
Module 3.1: SQL Server Reporting Services
|Basics of SSRS|
|Creating Visualization Using SSRS|
Module 3.2: SQL Server Integration Services
|Understanding the Basics of SSIS|
|Creating Packages to Integrate|
|Creating Project Using SSIS|
Module 4: Power BI
|Data Preparation and Modeling|
|Data Analysis Expressions (DAX)|
|Reports Development (Visuals in Power BI)|
Module 5: Data Analytics Using Python
|Introduction to Basic Statistics|
|Introduction to Mathematical Foundations|
|Introduction to Analytics & Data Science|
|Python Essentials (Core)|
|Operations with NumPy (Numerical Python)|
|Overview of Pandas|
|Cleansing Data with Python|
|Data Analysis Using Python|
|Data Visualization with Python|
|Statistical Methods & Hypothesis Testing|
Module 6: Tableau
|Data Handling & Summaries|
|Reports Development (Visuals in Tableau)|
Module 7: R For Data Science
|Using R with Databases|
|Data Visualization with R|
|Introduction to Statistics|
|Linear Regression: Solving Regression Problems|
Module 8: Alteryx
|Overview of the Alteryx Course and Fundamental Concepts|
|Using the Select Tool to Rename Fields, Change the Data Type|
|Understanding the User Environment and Alteryx Settings|
|Filtering Data/Data Processing|
|Blending/Joining Data from Different Sources|
Sign up for the Demo Session free Of Cost
You learn to work with a variety of tools that help you become an astute data analyst. Get Details on the tools learnt In the course
The course’s emphasis on imparting knowledge of the fundamentals of data analytics through hands-on experience means that students can effortlessly apply what they learn to a variety of projects and projects beyond the classroom. It is well worth it to join and put confidence in IIM’s abilities to advance your professional skills for your career. IIM Skills is trustworthy in the quality of their training and the value they offer and assistance in placements for all of their learners.
+919580740740, [email protected]
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DataMites is prominent among institutions in professional training because of the comprehensiveness, scope, and affordability of its offerings in the rapidly expanding field of analytics. DataMites provides an opportunity to learn Data Analytics Courses In Thailand for students.
Courses are available in Data Science, Data Analytics, Machine Learning, Data Mining, Tableau Associate, Text Mining, Python Programming, Deep Learning, and Minitab, to name a few. The fundamental objective of DataMites is to produce experts who are prepared to bravely face the challenges of the increasingly competitive analytics industry. To ensure that the candidates receiving our training receive the most up-to-date and useful information possible, we have specialists with extensive expertise and an industrial background design and update our training courses regularly. We have become a leading training provider thanks to our commitment to deliver excellent training at reasonable prices. One of our main roles in training is to provide individualized answers based on the learner’s needs. Our phrontistery’s top-notch instruction has benefited countless newbies, software experts, analytically-minded job-seekers, and multinational corporations.
Syllabus of Data Analytics Courses In Thailand
Basics of Data Analysis
- An Overview of Data Analysis: An overview of data analysis, its significance, and its practical applications.
- Preparing Data for Analysis Entails Using Appropriate Methods to Clean, Transform, and Organise Data.
- Missing values, outliers, and duplicates are just a few examples of the usual data problems that need to be identified and fixed.
- Excel, Python, R, and Other Commonly Used Data Analysis Tools and Software
- Background on the development of analytics and its effects on many sectors over time.
Analysis of One Variable
- Employing summary statistics to examine the mean and standard deviation of the data.
- Discussion and illustration of the central tendency of the measures (mean, median, and mode).
- Range, interquartile range, variance, and standard deviation are examined carefully as indices of data variability.
- Making and reading frequency charts to depict data distribution.
- Data distributions can be visually represented using a variety of chart types, such as histograms, bar charts, and pie charts.
Visual Data Analysis
- Line charts are used to show the progression of data over time.
- Column/Bar Graph: Constructing Bar Graphs and Column Graphs for Analysing Categorical Data.
- The use of waterfall charts to show the cumulative effects of data is investigated.
- How to read and create treemap charts to display hierarchical data.
- Box charts are useful for identifying trends and outliers in data.
- Understanding Python Objects
- An in-depth look at the basic data types in Python
- Performing Mathematical Operations Using Arithmetic Operators.
- provides a primer on the use of comparison operators in formal logic.
- In-depth examination of assignment operators for setting values of variables.
- Tutorial on Python Loops, covering the fundamentals of using while and for loops.
- Sets, set operations, and set comprehensions are covered in detail.
- Dictionary work includes learning how dictionaries work and how to use them effectively.
- Functional Generators: Defining and Implementing Generators.
- Definitions of functions can be expressed succinctly using lambda functions, which are introduced here.
- An Overview of the NumPy Library for Numerical Computation (An Introduction to NumPy).
- NumPy operations and functions.
- Matrix Operations
- The use of Pandas
CRIP-DM Model Module
- An Overview of the CRIP-DM Model, a Common Reference Implementation for Process Standardisation in Data Mining.
- The value of business knowledge in data analysis
- Understanding Data Methods
- Use requires processing, cleaning, and transforming raw data.
- Analysis via modeling construction and refinement.
- An Overview of Pandas’ Data Manipulation
- Data Analysis Features.
- Understanding Pandas Series
- DataFrames as Data Structures, Covering Both Data Frames and Series.
- Tips and tricks for cleaning and data arrangement with Pandas.
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3. The Knowledge Academy
The Knowledge Academy offers advanced certification in Data analytics courses in Thailand. This is a competitive provider of professional education that is developing numerous courses, particularly analytics courses in India. Their primary objective is to equip individuals with revolutionary competencies that will enhance their opportunities for employment as data analysts. The course incorporates every aspect necessary for enhanced learning.
The courses at Knowledge Academy are designed for students of any experience level. Students are urged to reach out to friendly instructors if they have any problems getting access to the course materials. They are prepared to provide timely assistance to all students in addressing any challenges and guaranteeing continuous access to all course materials. Courses in data analytics and artificial intelligence education fall under this category as well.
Knowledge Academy instructors are chosen for their extensive expertise in their respective fields and their ability to make the material they present interesting and relevant to the learner. Professional organizations like Axelos, APMG, The Open Group, PMI, APM, Microsoft, ISACA, and many more have accredited several of our courses, attesting to the high quality of our instruction and curriculum.
This essential data analytics curriculum equips students with the skills they’ll need to help businesses respond to shifting conditions, use data to guide decision-making and increase their competitive advantage. The Knowledge Academy is a good alternative for Data Analytics Courses In Thailand.
Syllabus of Data Analytics Courses In Thailand
- Algorithms Analysis:
- Probability and Statistics:
- Fundamentals Concepts:
- Programming Skills:
- Machine Learning:
- Tools and Applications:
- Functions in Data Analysis Expressions (DAX):
- Business Analytics:
- Language processing, text summarization, sentiment analysis, and clustering
After completing a well-structured data analytics course, students will feel confident working with data and will enhance their verbal and visual communication abilities so that they can effectively convey data analytics findings to a business team. They will have a firm grasp on the subject matter and will be able to utilize it for reasoning up their own decisions. Data analytics is a lucrative and promising field since it necessitates the development of skills that are in great demand in a variety of businesses. Additionally, they will refine their research abilities by determining which analytics paradigm to employ and providing an explanation for their choice, by a planned research query and the information at hand.
Simplilearn is an online learning centre that provides a platform for Data Analytics Courses In Thailand for learners in Thailand. Simplilearn is a platform for Learners can take advantage of Simplilearn’s Data Analytics courses from the comfort of their own homes in Thailand or anywhere else in the world to boost their employability. Professional instructors and hands-on projects help bring theories to life in data analytics courses offered in Thailand through an agreement with Purdue University and IBM.
The combination of blended learning is an outstanding option since it mixes traditional classroom instruction with independent study at the student’s own pace. The course is well-organized and discussed for learners, and the lecturers are knowledgeable, experienced, and interesting. Practical situations and practical exercises were incorporated into the curriculum.
Curriculum Covered in Data Analytics Courses In Thailand
- Analysis of Data
- Analyzing the Numbers
- Power BI and Tableau( Visualizing the data using Tableau and Power BI is also covered in this intensive Data Analytics Course curriculum)
- Modules for linear and logistic regression
- Business Guidance
- Analysis of Data in Excel
- R and Python (The fundamental concepts of Statistics basis, data analysis using Python and R languages, and communicating with databases using SQL)
- Visualization of Data
- Microsoft Excel
These course curricula by simplilearn designed by expert faculty which can help students advance their knowledge rapidly in their chosen fields of study.
Frequently Asked Questions of article Data Analytics Courses in Thailand
Q. What prominent programming languages are useful for Data Analytics?
The dominant programming languages applied in data analytics are as follows:
Data analytics will continue to prioritize Python proficiency as the preeminent skill set for a minimum of the next five years. Proficiency in Python, in conjunction with a robust aptitude for experimental analysis and quantitative reasoning, can lead to significant success in the field.
R has rapidly surpassed several programming languages to establish itself as one of the preeminent languages in the field of data science.
Design of an abundance of statistical models is possible with R. It is utilized by statisticians to conduct regression assignments. R also provides data visualization capabilities, including support for various types of infographics.
Scala is a highly prevalent functional programming language. It uses JVM. It is an optimal choice for individuals who frequently encounter large-scale datasets. Its JVM origins facilitate its integration with Java in data analytics.
In SQL, data is organized in the form of tables, where columns represent distinct attributes and rows reflect a variety of documents. It is an open-source application that is extensively utilized for managing inventories, logging, and data logistics, and it facilitates a complete environment for development.
Q. What varieties of Data Analysis exist?
The processing of information can be split down into multiple smaller stages, such as specifying what data is needed, assembling that data, analyzing it, and then presenting the findings visually.
Some common forms of data analysis include the following:
Text analysis, often known as data mining, is the practice of examining huge swaths of text for recurring themes or correlations, such as those found in survey responses from customers or comments made on social media. Key insights into perplexing datasets can be uncovered with the aid of text analysis.
Assessments of Statistics
Statistical analysis can examine both the global features of a numerical dataset and relevant subsets or samples from it. Data patterns can be uncovered with the use of descriptive statistics (think: growth charts) whereas inferential statistics seek out statistically significant relationships between variables.
The goal of diagnostic analytics is to delve further into the findings of statistical analysis to ascertain the reasons behind the observed connections. Diagnostic analysis can be used to determine the root cause of a phenomenon, such as a cluster of cart abandonments at the same point in the checkout process or a correlation between disease rates and environmental conditions.
Extrapolating or projecting numbers beyond the bounds of the current dataset is an example of predictive analytics.
Prescriptive analytics integrates all of the information gathered and recommends the appropriate action to take.
Q. Why is the programming language Python deemed the greatest for analytics?
Python is considered to be the most effective of these programming languages for data science, even though all of them are suitable. Among the numerous reasons why Python is among the finest are the following:
Python is considerably more scalable than Scala and R, among others. The scalability of the system is attributed to the flexibility it grants programmers. Its extensive collection of data science libraries, including Scikit-learn, NumPy, and Pandas, provides it an advantage over other programming languages. A sizable community of Python programmers contributes continuously to the language and assists novices in their Python development.
Conclusion of Data Analytics Courses in Thailand
The data-focused positions in tech companies are always open. Learning data analytics courses in Thailand will allow you to find work in many different fields.
Expertise in using data to inform decisions is in high demand in a variety of industries, including academia, banking, healthcare, and more. The data analytics industry is also highly segmented, so you can choose to specialize in advertising, commercial operations, or any other area that piques your interest.
Learning data analytics courses in Thailand or wherever you live can help to advance in your current role and open doors to more interesting projects elsewhere in your organization if you’re feeling stagnant.