CERTIFIED DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYST COURSE FEES IN MYANMAR

Live Virtual

Instructor Led Live Online

MMK 2,250,000
MMK 1,276,821

  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

MMK 1,125,000
MMK 731,705

  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA ANALYST ONLINE CLASSES IN MYANMAR

BEST DATA ANALYTICS CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

images not display images not display

WHY DATAMITES INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST CERTIFICATION IN MYANMAR

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain

MODULE 2: CLASSIFICATION OF ANALYTICS

• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics

MODULE 3: CRIP-DM Model

• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
Modeling, Evaluation, Deploying,Monitoring

MODULE 4: UNIVARIATE DATA ANALYSIS

• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.

MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS

• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot

MODULE 6: BI-VARIATE DATA ANALYSIS

• Scatter Plots
• Regression Analysis
• Correlation Coefficients

MODULE 1: PYTHON BASICS

• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators

MODULE 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions

MODULE 1 : OVERVIEW OF STATISTICS 

  • Introduction to Statistics
  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's Minimum Sample Size
  • Types of Sampling
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Multi stage Sampling
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution & Properties
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Critical Region
  • Types of Hypothesis Testing
  • Hypothesis Testing Errors : Type I And Type Ii
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test
  • Application of Hypothesis testing

MODULE 1: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis

MODULE 3: RANKING ANALYSIS

• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis

MODULE 4: BREAK EVEN ANALYSIS

• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis

MODULE 6: Time Series and Trend Analysis

• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity

MODULE 2: OPTIMIZATION MODELS

• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel

MODULE 4: DECISION MODELING

• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer

MODULE 1: MACHINE LEARNING INTRODUCTION

• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSSION

• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool

MODULE 3: ML ALGO: LOGISTIC REGRESSION

• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering

MODULE 6: ML ALGO: DECISION TREE

• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool

MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool

MODULE 1: DATABASE INTRODUCTION

• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)

MODULE 2: SQL BASICS

• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation

MODULE 3: DATA TYPES AND CONSTRAINTS

• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL)

• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table

MODULE 5: SQL JOINS

• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank

MODULE 6: SQL COMMANDS AND CLAUSES

• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries

MODULE 7: DOCUMENT DB/NO-SQL DB

• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management

MODULE 1: BIG DATA INTRODUCTION

• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE

• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort

MODULE 3: PYSPARK FOUNDATION

• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE

• Introducing Spark SQL
• Spark SQL vs Hadoop Hive

MODULE 1: TABLEAU FUNDAMENTALS

• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies

MODULE 2: POWER-BI BASICS

• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION

MODULE 3: DATA TRANSFORMATION TECHNIQUES

• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values

MODULE 4: CONNECTING TO VARIOUS DATA SOURCES

• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model

OFFERED DATA ANALYST COURSES IN MYANMAR

DATA ANALYST TRAINING COURSE REVIEWS

ABOUT DATAMITES DATA ANALYST TRAINING IN MYANMAR

According to an Acumen Research and Consulting report, the data analytics market size is expected to reach USD 329.8 Billion by 2030 at a growing CAGR rate of 29.9%. The demand for data analytics courses in Myanmar has been increasing in recent years due to the rapid growth of digital technologies and the increasing amount of data generated by various industries. With businesses adopting data-driven strategies, there is a need for skilled professionals who can analyze and interpret data to make informed decisions.

DataMites is a renowned provider of data analytics course in Myanmar that offers the Certified Data Analyst course, which equips beginners and intermediates with a comprehensive understanding of data analytics. The program covers various areas such as data science basics, statistics, visual analytics, data modeling, and predictive modeling, making it an all-inclusive curriculum that does not require coding expertise. The main objective of the course is to prepare students for a career in data analytics by training them to identify valuable insights in unstructured data and leverage them to make informed business decisions.  The course has received approval from IABAC, a globally recognized organization, which further enhances its reputation and industry acceptance and students get IABAC certification at the end of the training. To meet industry-related requirements, DataMites provides students with a specialized syllabus, mock tests, high-quality study materials, job placement, and internship programs.

The Certified Data Analyst Course in Myanmar is a six-month course that comprises two months of live online instruction, two months of practical projects, and two months of the internship experience. This approach helps students apply their learned concepts in real-world scenarios, thus increasing their chances of securing entry-level analytics jobs. The course emphasizes the entire data analysis process, from data cleaning to visualization, and is taught by highly qualified instructors who can extract invaluable insights from raw data.

The career scope for data analysts in Myanmar is quite promising due to the increasing demand for data-driven decision-making in various industries. Data analysts play a crucial role in helping organizations gain insights from data, identify trends, and make informed decisions. Some of the industries where data analysts are in high demand in Myanmar include banking and finance, healthcare, retail, e-commerce, and telecommunications. The salary of data analysts in Myanmar ranges from MMR 6,058,300 Per year according to a World Salaries report. Join DataMites for concrete knowledge regarding the domain.

Along with the data analyst courses, DataMites also provides python training, deep learning, data engineer, data analytics, r programming, mlops, artificial intelligence, machine learning and data science courses in Myanmar.

ABOUT DATA ANALYST COURSE IN MYANMAR

Data analytics is the process of examining data sets to extract meaningful insights and draw conclusions about the information they contain. It involves applying various statistical and computational techniques to explore and analyze data, identify patterns and trends, and generate insights that can be used to inform decision-making.

While there is some overlap between data analytics and data science, the two are distinct disciplines. Data science is a broader field that encompasses data analytics, as well as other areas such as machine learning, artificial intelligence, and data engineering. Data analytics focuses on analyzing data to generate insights and inform decision-making, whereas data science involves using a range of techniques to extract insights from data and build predictive models.

Data analytics is a rapidly growing field, and there are opportunities for people with a wide range of backgrounds and skill sets to pursue a career in this area. However, to succeed in data analytics, it is important to have a strong foundation in data analysis, statistics, and programming.

Some essential skills for data analytics include:

  • Data analysis and visualization
  • Statistical analysis
  • Programming skills (such as Python, R, or SQL)
  • Knowledge of machine learning techniques
  • Critical thinking and problem-solving skills
  • Communication and presentation skills

Some common tools and techniques used in data analytics include:

  • SQL for data manipulation and querying
  • Python or R for data analysis and modeling
  • Excel for data analysis and visualization
  • Tableau or Power BI for data visualization and business intelligence
  • Machine learning algorithms for predictive modeling and pattern recognition

The fee would differ from institute to institute and the level of training you are looking for. The Data Analytics training fee in Myanmar ranges from MMK 1026908.85 to MMK 2310544.91.

DataMites is the ideal choice for those interested in pursuing a career in the analytics industry. The instructors are experienced and industry-focused, and the course structure is well-designed. We offer hands-on training through projects and internships, providing practical experience.

There are numerous employment options in various industries, such as finance, healthcare, e-commerce, and marketing, for those pursuing a career in data analytics. Popular job titles in this field include data analyst, business analyst, data scientist, data engineer, and data architect, among other roles.

Data analytics finds application in numerous industries such as healthcare, finance, marketing, e-commerce, sports, and social media, among others. It helps in streamlining business operations, enhance customer experience, formulate focused marketing strategies, and make data-driven decisions across various sectors.

 The salary of data analysts in Myanmar ranges from MMR 6,058,300 Per year according to a World Salaries report.

FAQ’S OF DATA ANALYST COURSE IN MYANMAR

DataMites provides top-notch certification training in data analytics in South Africa that enables individuals to showcase their proficiency in the field. This program prepares individuals to assist organizations in comprehending data and making informed decisions, which can lead to career opportunities with prominent multinational companies. Obtaining a certification from DataMites signifies an individual's capacity to execute specific job responsibilities in compliance with professional standards, making it a more valuable certification compared to a basic data analytics certificate.

For individuals who aspire to pursue a career in data analytics or data science, the Certified Data Analyst Course offered by DataMites in South Africa is an exceptional option. This program is a no-coding course that does not demand any previous programming experience, making it ideal for beginners. The training curriculum is methodically structured to offer an all-encompassing comprehension of the subject matter. If you are fascinated by analytics and eager to delve deeper into this field, enrolling in this course is an excellent way to expand your knowledge.

DataMites is a renowned institution that provides excellent data analytics courses. Here are some reasons why you should consider opting for a data analytics course from DataMites:

Comprehensive Curriculum: DataMites' data analytics courses have a comprehensive curriculum that covers all essential topics related to data analytics. They provide in-depth knowledge of concepts, tools, and techniques used in data analytics, making the course well-structured and informative.

Industry-Relevant Training: DataMites' data analytics courses are designed keeping in mind the current industry trends and requirements. They equip you with the skills and knowledge that are in high demand in the job market.

Experienced Trainers: DataMites' trainers are experienced professionals who have extensive knowledge of the data analytics field. They provide personalized attention and guidance to each student, ensuring that they understand the concepts thoroughly.

Hands-on Learning: DataMites' data analytics courses provide hands-on learning, enabling you to gain practical experience in data analytics. You will work on real-world projects, which will help you apply the concepts you have learned in a practical setting.

Certification: DataMites' data analytics courses provide industry-recognized certifications, which can enhance your job prospects and improve your career growth.

DataMites' Certified Data Analyst Training is an excellent option due to its no-coding curriculum that requires no prior programming experience and its comprehensive training program that provides hands-on experience in the field of data analytics.

Depending on the type of training you choose, DataMites' certified data analytics training costs can change. The cost of a certified data analytics course in London, however, can normally range from MMK 1,189,747 to MMK 1,458,113.

You will receive six months of data analytics training from DataMites, including 20 hours of instruction every week.

If you aspire to pursue a career as a data analyst, enrolling in DataMites' Certified Data Analyst Training is a wise decision. The curriculum is designed to provide individuals with comprehensive knowledge, hands-on experience, and industry-recognized certifications, enabling them to kickstart their data analyst career from scratch with confidence.

The Certified Data Analytics Training by DataMites provides a Flexi-Pass option that allows candidates to attend any relevant session within three months for revision or clarification purposes. This flexible arrangement enables candidates to select sessions that cater to their specific requirements and resolve any queries they may have during the training period.

To facilitate ease and convenience for our clients, we provide multiple payment options, including cash, debit card, check, credit card (Visa, Mastercard, American Express), PayPal, and net banking. You can select the payment method that aligns with your preferences and make a secure and hassle-free payment.

Yes, With our accreditation from IABAC®, you can rest assured that your relevant skills and abilities will be recognized internationally. Our training program meets the requisite standards, providing you with the confidence that your accomplishments will be acknowledged worldwide.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

View more

OTHER DATA ANALYST TRAINING CITIES IN MYANMAR

Global DATA ANALYTICS COURSES Countries

popular career ORIENTED COURSES

DATAMITES POPULAR COURSES


HELPFUL RESOURCES - DataMites Official Blog