Data Analytics Training in Singapore

Credo Systemz offers Data Analytics training courses to gain the knowledge of data analytics using expert trainers.

Our data analytics course covers skills of collecting, cleaning, and analyzing data to generate meaningful insights.
Learn the skills of statistics, SQL, Excel, data visualization and Power BI.
Practical based training, Real-time projects, placement assistance and career guidance.

Flexible Mode of Training

Online Training
Corporate Training
Class Room Training
1V1 / Personal Training

Data
Analytics

Case Studies and Projects15+
Hours of Practical Training80+
Placement Assurance100%
Expert Support24/7
Support & AccessLifetime
CertificationYes

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Data Analytics Training

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What is Data Analytics?
Types of Data Analytics
The Data Analytics Process
Importance of Data Analytics in Business
Tools and Technologies in Data Analytics
Real-World Examples
Career scope and job roles in Data Analytics

Introduction to Excel
Understanding Cell Referencing
Basic Arithmetic and Logical Operations
Data Cleaning and Formatting
Data Validation & Drop-downs
Flash Fill and AutoFill
Functions and Formulas
Array Formulas & Dynamic Arrays (FILTER, SORT, UNIQUE)
Pivot Tables and Charts
Slicers and Timelines for Interactive Filtering
Conditional Formatting
Dynamic Formatting Based on Cell Value or Date
Dashboard Creation
Combining Charts, KPIs, and Sparklines
Linking Pivot Tables with Slicers
Introduction to Macros and VBA
Workbook Protection and Data Security

Hands-on Practical Exercises

Clean and Analyze Raw Sales Data
Create Interactive Employee Dashboard
Monthly Report Automation using Formulas and Pivot Tables
KPI Dashboard for Marketing Metrics

Introduction to Oracle Database
Introduction to RDBMS (MySQL, PostgreSQL, SQL Server)
Understanding Tables, Rows, Columns
SQL Syntax, Case Sensitivity, Comments
SQL Commands
Using Aliases
Filtering and Logic
Aggregations & Grouping
Difference between WHERE vs HAVING
Joins – Inner, Left, Right, Full Outer, Self, Cross Join
Subqueries & Nested Queries
Window (Analytic) Functions
DML – Data Manipulation Language
DDL – Data Definition Language
Time Series Analysis
Revenue Analysis with Filters and Joins
Customer Segmentation using SQL

Hands-on Practical Exercises

Create & Query a Sales Database
Build a Regional Revenue Report
Customer Insights
Employee Performance Ranking

Importance of Statistics in Data Analytics
Descriptive Statistics: Mean, Median, Mode, Range, Variance, Std. Deviation
Data Summarization
Data Visualization
Using Visualizations for Outlier Detection
Probability Concepts
Types of Events
Addition & Multiplication Rules
Conditional Probability
Probability Distributions
Central Limit Theorem
Inferential Statistics
Hypothesis Testing
Correlation and Regression
Exploratory Data Analysis with Statistics

Hands-on Practical Exercises

Customer Satisfaction Analysis
Ad Spend vs Sales
Product Quality Check
Delivery Time Comparison

Introduction to Power BI
Installing Power BI Desktop
Power BI Interface
Data Loading & Importing from Various Sources
Understanding Power BI File Types
Power Query – Data Transformation
Cleaning and Shaping Data
Filtering and Sorting Data
Unpivoting and Pivoting Data
Data Modeling
Creating Date Table & Time Intelligence
DAX Basics: SUM, COUNT, DISTINCT, AVERAGE
Logical, Aggregation and Filter Functions
Data Visualization: Bar, Column, Line, Pie, Donut
Advanced Charts: TreeMap, Funnel, Waterfall, Gauge, KPI
Slicers and Filters
Dashboard and Report Design
Power BI Service
Row-Level Security

Hands-on Practical Exercises

Customer Segmentation Report
E-commerce Product Performance
Marketing Campaign Analysis
Sales Dashboard

Introduction to Python
Why Python for Data Analytics?
Python Syntax and Code Structure
Arithmetic & Logical Operators
Conditional Statements
Loops & Functions
Error Handling
Data Structures in Python
NumPy – Numerical Python
NumPy Arrays vs Lists
Statistical Functions: mean(), std(), sum()
Pandas – Data Handling Library
Visual EDA with Pandas
Indexing, Filtering, and Slicing
GroupBy and Aggregations
Sorting, Renaming Columns
Data Cleaning and Preparation
Data Visualization with Python
Statistical Analysis with Python

Hands-on Practical Exercises

Analyze sales data to find top-performing products
Clean messy customer data and find duplicates
Segment customers by spending habits using Pandas
Automate data reports using Python scripting

Handling Missing Data: Imputation, Deletion
Data Normalization and Standardization
Detecting and Handling Outliers
Feature Engineering
EDA: Distribution Analysis, Correlation, Feature Selection

Hands-on Practical Exercises

Clean and prepare a messy dataset for analysis.
Perform a thorough EDA, identifying key trends and insights.

AI for Data Analytics: Automated Insights, Predictive Analytics
Using AI tools like ChatGPT for Data Analysis
AI-Powered Data Wrangling
Predictive Models: Introduction to Basic Machine Learning Algorithms

Hands-on Practical Exercises

Use AI tools to automate data cleaning or feature engineering on a dataset.
Build a simple predictive model using an AI tool.

Flexible Mode of Training and Payment

Data Analytics Course FAQs

Yes, our data analytics training is suitable for non-IT professionals from different backgrounds such as commerce or MBA. We start from the basics and help you understand the fundamentals of data analytics clearly.

Yes! We offer lifetime access to all course materials, practical exercises, projects, and live recordings so that you can continue to learn and revise anytime during your career journey.

Yes. Our Data Analytics online training provides live, expert-led sessions. If you miss a class, we provide access to recorded sessions to review the topics later at your convenience.

Yes. Credo Systemz focuses on both technical and communication skills. We include dedicated sessions on soft skills and professional communication to make you job-ready.

We accept multiple convenient payment options:

Cash
Credit/Debit Card
Cheque
UPI Services

Essential technical skills include:

Excel/Google Sheets: Pivot tables, formulas, charts
SQL: Query databases to extract and analyze data
Python/R: Data cleaning, analysis, visualization
Data Visualization: Power BI, Tableau, or Matplotlib/Seaborn
Statistics: Mean, median, mode, standard deviation, probability

Credo Systemz offers expert-led Data Analytics training that includes over 60+ hours of live sessions to master the core skills required to become a professional analyst.

Yes! Even if you don’t have a technical background, you can become a successful data analyst by learning key skills like Excel, SQL, Python, and Data Visualization. Our course starts from the fundamentals.

Data Analytics focuses on examining existing data to find patterns, trends, and actionable insights.

Data Science goes beyond analytics—it includes predictive modeling and machine learning to forecast future trends and outcomes.

Career paths for data analytics professionals include:

Data Analyst
Business Intelligence (BI) Analyst
Reporting Specialist
Business Analyst
Data Visualization Specialist

Industries such as IT, Finance, Healthcare, and Retail actively hire data analytics experts for reporting, dashboard creation, and strategic decision-making.