CERTIFIED DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYST COURSE FEES IN NETHERLANDS

Live Virtual

Instructor Led Live Online

Euro 1,850
Euro 1,055

  • 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

Euro 930
Euro 604

  • 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

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

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UPCOMING DATA ANALYST ONLINE CLASSES IN NETHERLANDS

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.

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WHY DATAMITES INSTITUTE FOR DATA ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST CERTIFICATION IN NETHERLANDS

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 NETHERLANDS

DATA ANALYST TRAINING COURSE REVIEWS

ABOUT DATAMITES DATA ANALYST TRAINING IN NETHERLANDS

According to the Market Research Future report, the market size of data analytics in the Netherlands is anticipated to reach USD 303.4 Billion by the year 2030. Data analyst demand in the Netherlands is very high, and it is expected to continue growing in the coming years. The country has a thriving tech industry and is home to many multinational companies, startups, and research organizations that rely on data analytics to make informed business decisions.

DataMites is a prominent provider of data analytics course in the Netherlands, catering to beginners and intermediates in the field with its Certified Data Analyst course. Having trained over 50,000 students worldwide, DataMites offers an all-encompassing curriculum that imparts a solid grounding in data analytics, encompassing data science fundamentals, statistics, visual analytics, data modeling, and predictive modeling, all without requiring coding knowledge. The program is specifically geared towards preparing students for a career in data analytics by teaching them how to discern valuable insights in unstructured data and use them to make informed business decisions. DataMites offers students a specialized syllabus, mock tests, high-quality study materials, job placement and internship programs etc to meet industry-related requirements. 

The six-month Certified Data Analyst Training course at DataMites consists of two months of live online instruction, two months of practical projects, and two months of internship experience to apply the learned concepts in real-world scenarios, significantly enhancing the chances of securing entry-level analytics jobs. With an emphasis on teaching the entire data analysis process, from cleaning to visualization, DataMites boasts highly qualified instructors capable of extracting invaluable insights from raw data. Furthermore, the course has received approval from IABAC, a global organization, adding to its reputation and acceptance within the industry.

The future of data analytics in the Netherlands is expected to be very bright. The Netherlands has a thriving tech sector and a highly skilled workforce, making it an ideal location for businesses to invest in data analytics. One of the major trends in data analytics in the Netherlands is the increasing use of machine learning and artificial intelligence (AI) in business applications. This is driven by the availability of large datasets and advanced algorithms, which allow companies to gain valuable insights into customer behaviour, market trends, and other important factors. Join DataMites for Certified Data Analyst Course in the Netherlands to have a remarkable career.

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 Netherlands.

ABOUT DATA ANALYST COURSE IN NETHERLANDS

Data analytics refers to the process of examining and interpreting data using statistical and computational techniques to extract useful insights, patterns, and trends. It involves collecting, cleaning, transforming, and modeling data to derive meaningful insights that can be used to make informed decisions.

While data analytics and data science share some similarities, they are different in several ways. Data analytics focuses on extracting insights and patterns from structured data using statistical and computational techniques. Data science, on the other hand, is a more comprehensive field that encompasses data analytics and other related fields such as machine learning, artificial intelligence, and big data.

Yes, a career in data analytics is open to everyone, regardless of their educational background or work experience. However, having a degree in a related field such as computer science, statistics, or mathematics, and relevant work experience can be an added advantage.

Some of the essential skills required for data analytics include proficiency in programming languages such as Python, R, and SQL, data visualization, statistical analysis, data cleaning and transformation, and problem-solving.

Some of the frequently used tools and techniques in data analytics include Excel, Tableau, Python, R, SQL, data warehousing, data mining, machine learning, and predictive modeling.

The cost of Data Analytics training can vary depending on the institute and the level of training desired. In the Netherlands, the fees for Data Analytics training can range from 8986.51 EUR to 20219.65 EUR, with different institutes offering different rates.

DataMites is an ideal choice if you aspire to establish a career in the analytics industry. The instructors are highly experienced and industry-focused, and the course syllabus is thoughtfully structured. In addition to theoretical concepts, our program includes hands-on training through projects and internships, enabling you to gain practical experience.

The demand for data analytics professionals is growing rapidly, and there is a shortage of skilled professionals in the field. Therefore, there are plenty of job opportunities in data analytics across various industries, including healthcare, finance, retail, and marketing.

There are several courses available for learning data analytics, ranging from short-term certificate courses to full-time degree programs. Some of the popular courses include Data Analytics Certification, Data Science Bootcamp, and Masters in Data Analytics.

The salary of a data analyst in the Netherlands ranges from EUR 60,000 Per Year according to a Glassdoor report.

FAQ’S OF DATA ANALYST COURSE IN NETHERLANDS

DataMites provides exceptional certification training for data analysts in the Netherlands, which validates your proficiency in data analytics with concrete evidence. Our training equips you with the necessary skills to assist organizations in interpreting data and making informed decisions, thereby opening up opportunities to work with top multinational companies. A certification from DataMites indicates your capability to fulfil specific job roles as per industry standards, making it more valuable than a basic data analytics certificate.

DataMites offers an outstanding option for individuals interested in pursuing a career in data analytics or data science with their Certified Data Analyst Course in the Netherlands. This no-coding course does not require any previous programming experience, making it an ideal option for beginners. The course curriculum is structured systematically, ensuring that you gain a thorough understanding of the subject matter. If you are curious about analytics, enrolling in this course is an excellent way to delve deeper into the field.

DataMites, a worldwide institution for data science, has obtained recognition from the International Association of Business Analytics Certifications (IABAC). By employing a three-phase learning process and incorporating real-world projects and case studies into their training, they have trained over 50,000 individuals in data science and analytics, offering top-notch education. Upon completion of the course, candidates receive an internationally recognized IABAC Data Analytics Certification, and they may also intern for Rubixe, a prominent AI startup.

The Certified Data Analyst curriculum offered by DataMites is a high-quality data analytics program that has earned accreditation from the internationally renowned IABAC. Upon completion of this program, you will receive credentials from the IABAC, which will give you valuable industry recognition. The optimal approach to kickstart your career in data analytics is to acquire the DataMites Certified Data Analyst certification.

The cost of DataMites' certified data analytics training can vary depending on the type of training you select. Typically, in the Netherlands, the cost of a certified data analytics course can range from 686 EUR to1,280 EUR depending on the mode of training.

DataMites provides a data analytics training program that spans six months and comprises 20 hours of instruction per week.

The DataMites Certified Data Analyst Training is an exceptional choice if you are contemplating a career as a data analyst. Our training program is meticulously crafted to offer you a comprehensive curriculum that will empower you with the skills, certifications, and confidence to initiate your data analyst journey from the very beginning. With our program, you can be confident that you will acquire the necessary knowledge and expertise to excel in this field.

The DataMites Certified Data Analytics Training comes with a Flexi-Pass option that enables candidates to attend any applicable sessions within a three-month period for the purpose of clarification or review. This grants candidates the freedom to select sessions that correspond to their specific requirements and address any concerns or inquiries they may have throughout the training duration.

To provide you with the utmost convenience, we offer several payment options, including cash, debit card, check, credit card (Visa, Mastercard, American Express), PayPal, and net banking. You may opt for the payment method that aligns with your preference and make your payment securely and effortlessly.

Yes, by obtaining accreditation from IABAC®, we guarantee the acknowledgement of your pertinent skills and expertise on an international level. You can trust that your training has fulfilled the necessary criteria, and your achievements will be recognized 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.

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