google-site-verification: googlef3ce2171c703f847.html

×

Data Analytics Course in Chennai

India’s 1st AI-Driven IT Training – Credo Systemz

Credo Systemz data analytics Course in Chennai is the best training course to master the skills of data analytics with AI. We offer practical oriented data analytics training in Chennai to build the analytics career with advanced Excel skills.

Live interactive training to gain the technical skills for Data Analytics
Skilled trainers to guide the aspirants throughout the data analytics training
Practical training in data analysis tool and techniques to become a data analyst
To master Predictive Analytics, Data Visualization, Big Data, Natural Language Processing

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
Skill LevelAll
LanguageEnglish / Tamil

Get to do Industrial Recognized Projects &
stay ahead in the job market !!

Sales Data Analysis

Analyze historical sales data to identify trends, revenue patterns, and key performance drivers.
Customer Segmentation

Categorize customers into distinct groups based on purchasing behavior and demographics to enable targeted marketing strategies.
E-commerce Product Analysis

Evaluate product performance across an e-commerce platform to identify best sellers, under performers, and optimization opportunities.

Data Analytics Training Feedback | Best Data Analytics Training Institute in Chennai

Data Analytics Training with AI

Download Syllabus

What is Artificial Intelligence (AI)?
Introduction to AI in Data Analytics
Evolution of AI in the Analytics Industry
Real-Life Use Cases
Benefits of Using AI in Data Analytics
Understanding Prompts and AI Outputs in Analytics
How Data Analysts Use AI Tools Today

Overview of AI Tools in Data Analytics

Copilot for SQL/Python
ChatGPT for Analytics
Codeium for Jupyter & Notebooks
Tabnine
Power BI with Copilot

Setting Up AI Tools for Data Analytics

Copilot for VS Code & Jupyter Notebooks
ChatGPT Setup for Analysts
Power BI Copilot Activation
AI Access in Browser-based Tools
Basic Prompt Engineering Tips

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

AI in Action

Use Copilot or ChatGPT to create formulas and charts.
AI suggests formatting and cleaning steps.
Automate tasks with AI-generated macros.

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 Join, Left Join, Right Join, Full Outer Join, Self Join, Cross Join
Subqueries & Nested Queries
Window (Analytic) Functions
Data Manipulation Language – DML
Data Definition Language – DDL
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

AI in Action

Auto-complete SQL with Copilot/ChatGPT
Write SQL using plain English with AI tools.
Get instant query fixes and JOIN suggestions.
Use AI for quick data segmentation and 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

AI in Action

Summarize data with AI tools.
Detect outliers and trends easily.
Use AI for EDA and visual reports.

Introduction to Power BI
Installing Power BI Desktop
Power BI Interface
Data Loading
Importing Data 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
Basic DAX Functions: – SUM, COUNT, DISTINCT, AVERAGE
Logical Functions
Aggregation and Filter Functions
Data Visualization
Creating Basic Charts: 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

AI in Action

Use Copilot to create visuals and DAX with text prompts.
AI visuals: Key Influencers, Q&A, Decomposition Tree.
Auto-suggest layouts and filters with AI.

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

AI in Action

Generate Python code using plain instructions.
Clean and analyze data with AI help in Pandas/Numpy.
Integrate OpenAI or Azure ML for smart analytics.

Flexible Mode of Data Analytics Training and Payment

FAQs

Yes, our data analytics course covers the necessary modules to build the knowledge of data analytics in 3 months. The trainers offer live sessions to achieve the industrial skills of data analytics.

According to the Glassdoor report, The total pay for a Data Analyst is ₹5,50,000 per year in the Chennai area. The average salary of any data analyst is ₹5,00,000 per year.

The essential skills required to become data analyst are:

Data Manipulation & Analysis skills include SQL, Excel, Python (Pandas, NumPy)
Knowledge of Data Visualization using Power BI, Tableau, Matplotlib, Seaborn
Statistical Analysis to perform Descriptive & Inferential Statistics
Data Cleaning & Preparation to Handle missing values, data transformation
Business Intelligence to Understand KPIs, dashboards
Machine Learning Basics like Regression and classification.

No, Credo Systemz data analytics course offers structured learning and industrial practice using skilled experts. We focus on Key challenges and provide in-depth training to understand and gain the skills like,

Understanding data structures and SQL
Learning Python or R for data analysis
Mastering statistics and probability
Gaining experience with visualization tools

In data analytics, coding knowledge is not mandatory but beneficial. It depends on the job roles and level of expertise, such as:

For Basic roles, minimal coding is required with Excel, SQL, Power BI/Tableau
Advanced roles need Python (Pandas, NumPy) and R programming knowledge
Big Data roles require Spark, Hadoop, Cloud platforms

Yes, data analytics is a promising career due to various growth opportunities in different sectors like finance, healthcare, marketing, and tech.

As Organizations rely on data-driven decision-making, data analysts are 8n demand with Competitive pay across industries. From data analyst, move on to various job roles like Data Scientist, BI Analyst, or Data Engineer.

Data Analytics Course Testimonials

Anirudh Srinivas

Senthil Kumar

Arjun Krishnan

Anitha

Pankaj Kumar

Ajay Julian

Srikumar

Vidhusana

Raghavi

Aneesa Banu

Call Now Button