AI-Powered Data Analytics Course & Internship in Chennai
Master the complete data analytics journey with a structured 150-day learning path covering Python, MySQL, NumPy, Pandas, ETL, Power BI, Snowflake, PySpark, Linux, Cloud Storage, Pipeline Modelling, Schema Design and a 25-day project at UNIQ Technologies.
Why Choose a Data Analytics with Python Course & Internship in Chennai?
Looking for a Data Analytics course in Chennai that combines Python, MySQL, Pandas, NumPy, ETL, Power BI, Snowflake, PySpark, Linux, cloud storage, pipeline modelling, schema design and hands-on project experience? The program at UNIQ Technologies is designed for students, freshers and aspiring data professionals.
From Database Extraction to Power BI Dashboards
Data analysts transform raw business records into visual reports, cloud data warehouse models, and executive insights using SQL, Pandas, Snowflake and Power BI.
Python Programming
Master Python syntax, data structures, OOP, file processing and automated data scripts.
MySQL Database
Execute SQL SELECT queries, joins, subqueries, grouping, aggregate functions and data filtering.
NumPy & Pandas
Perform numerical array computing, DataFrame wrangling, data cleaning and missing-value imputation.
ETL Concepts
Understand Extract, Transform and Load workflows, source-to-target mapping and data integration.
Power BI Visualization
Create interactive reports, business dashboards, charts, filters and executive visual insights.
Snowflake Cloud Warehouse
Query cloud databases, design analytical schemas, and manage cloud data warehouse workloads.
PySpark Big Data
Process large-scale distributed datasets using Spark DataFrames, transformations and actions.
Linux Fundamentals
Work with command-line tools, file permissions, system processes and cloud server navigation.
Cloud Storage
Organize and query unstructured/structured object files in modern cloud storage environments.
Pipeline Modelling
Design data ingestion, transformation stages, and multi-step analytics pipeline workflows.
Schema Design
Design relational models, dimensional schemas, star/snowflake warehouses, and data marts.
Data Analytics Capstone Project
Connect Python, SQL, ETL, Snowflake, Power BI and PySpark in an intensive 25-day capstone project.
Program Objective
Provide a comprehensive pathway connecting programming, SQL, ETL, business intelligence, cloud data platforms and distributed processing for high-demand analytics roles.
Who Can Join Data Analytics Training?
The program starts with core fundamentals and moves towards full stack development—designed for anyone eager to build a career in software development.
BE / B.Tech Graduates
Engineering graduates seeking careers in Data Analytics, BI, and Data Engineering fundamentals.
BCA & MCA Graduates
Computer application graduates ready for practical Python, SQL, Power BI and Snowflake skills.
B.Sc & M.Sc Graduates
Science graduates interested in data wrangling, business insights and cloud data platforms.
Aspiring Data Analysts
Learners focused on building, reporting, and visualizing end-to-end business insights.
Aspiring BI Professionals
Professionals targeting interactive reporting, dashboard design, and data presentation.
Aspiring Data Engineers
Learners interested in ETL pipelines, schema design, PySpark, and cloud data warehousing.
Final-Year Students & Freshers
Students seeking hands-on project experience before entering IT recruitment.
Career Switchers
Professionals looking to transition into high-growth data operations and analytics roles.
Data Analytics Roadmap
A structured learning path that moves from fundamentals and backend frameworks to AI, cloud concepts, professional tools and job preparation.
Learning Path
Course Modules
Python Programming
Python is the primary programming language for modern data analysis. Students build a strong scripting foundation to automate data tasks.
Key Topics
What you'll learn
Python Fundamentals
Variables, data types, operators, conditionals and loops
Data Structures
Lists, tuples, sets, dictionaries and string manipulations
Functions & Modules
Writing reusable functions, modules, packages and file handling
Data Processing
Object-oriented programming and automated data processing scripts
Learning Focus
Python skills form the foundation for Pandas data wrangling, PySpark big data, and automated ETL.
A structured path. No rushed learning.
The learning program distributes time across programming, databases, backend development, AI, professional tools, and career preparation.
Overall Program
The duration is intentionally spread across the complete learning journey instead of compressing the syllabus into a short-term crash course.
Python Programming
ProgrammingMySQL Database
DatabaseNumPy & Pandas
WranglingETL Concepts
Data IntegrationPower BI Visualization
BI & DashboardSnowflake Cloud Warehouse
Cloud WarehousePySpark Big Data
Big DataLinux Fundamentals
SystemsCloud Storage
Cloud StoragePipeline Modelling
ArchitectureSchema Designs
Schema DesignData Analytics Project
Capstone ProjectCore programming receives one of the largest portions of the learning timeline.
Approximate days across frontend, core programming, databases, and web foundations.
Overall program duration covering technical and career preparation.
What Skills Can You Develop During the Full Stack Internship?
Progress through the syllabus and understand how the major parts of a modern application connect—from the user interface to backend services and databases.
Ingestion & Extraction
Extract raw business data using SQL queries, MySQL databases, and Python connectors.
Wrangling & Data Platform
Clean data with Pandas, build ETL pipelines, and load data into Snowflake cloud warehouses.
Big Data & Visualization
Process big datasets using PySpark and build interactive Power BI dashboards for business insights.
Supporting skills for modern development
The core application stack is supplemented by exposure to modern development practices, cloud technologies, AI and software delivery tools.
Practical Data Analytics Training for Freshers
Freshers often face a particular problem when applying for their first software job: employers expect practical understanding even when candidates have no professional experience. An internship-oriented training environment helps bridge this gap.
At UNIQ Technologies, the emphasis is on learning concepts through coding and practical implementation rather than depending exclusively on theory.
Students should be able to explain:
Essential topics for fresher technical interviews
How to perform data cleaning and transformation in Pandas
Handling missing values, deduplicating records, reshaping columns, and preparing DataFrames.
How SQL queries aggregate and combine business datasets
Writing multi-table joins, GROUP BY aggregations, and CTEs to extract analytical datasets.
How to build interactive dashboards in Power BI
Designing reports, KPI cards, visual slicers, and charts that present key business metrics.
How Snowflake manages cloud data warehouse workloads
Querying cloud data tables, creating schemas, and managing scalable virtual warehouses.
How to run source-to-target ETL processing
Extracting raw data, transforming schema data types, and loading clean analytical tables.
How PySpark processes large-scale distributed data
Using Spark DataFrames and distributed transformations to process large data volumes.
How to design Star and Snowflake schemas
Structuring Fact and Dimension tables for fast querying and reporting performance.
How to build an end-to-end data analytics project
Combining Python extraction, SQL, ETL, Snowflake, PySpark, and Power BI into a single workflow.
Full Stack Projects That Connect the Full Stack
Project-based learning is an important part of becoming comfortable with Full Stack development. A practical project helps students understand how individual technologies work together as one complete application.
Project Architecture
One application. Multiple technologies. One workflow.
Data Extraction
MySQL + Python
Extract raw transactional datasets from SQL databases.
Wrangling & ETL
Pandas + ETL Engine
Clean, transform schema fields, and run source-to-target ETL.
Cloud Warehousing
Snowflake Cloud Platform
Load transformed data into Snowflake data warehouses and star schemas.
Big Data Processing
PySpark DataFrames
Aggregate large-scale data records using PySpark distributed compute.
BI Dashboards
Power BI Reports
Deliver interactive visual dashboards and business insight reports.
Data Analytics Career Opportunities
Depending on skills, project knowledge, interview performance, and employer requirements, learners can explore various entry-level opportunities across the software industry.
Data Analyst
Junior Data Analyst
Python Data Analyst
Business Intelligence Analyst
BI Analyst
Reporting Analyst
Data Operations Analyst
SQL Analyst
Junior Data Engineer
ETL Developer
Analytics Associate
Frequently Asked Questions
Everything you need to know about the internship, learning path, technologies, practical training and career preparation.
A Data Analytics course teaches learners how to collect, clean, transform, analyze and visualize data to generate useful business insights.
UNIQ Technologies offers a Data Analytics with Python program covering Python, MySQL, NumPy, Pandas, ETL, Power BI, Snowflake, PySpark, Linux, cloud storage, pipelines and schema design.
The course has a total duration of 150 days.
Yes. Python is a major part of the program and is allocated 35 days.
Python provides powerful tools for data manipulation, analysis, automation and visualization, serving as the foundation for libraries such as NumPy and Pandas.
Yes. MySQL is included for 30 days.
SQL allows analysts to retrieve, filter, join and aggregate data stored in relational databases.
Yes. NumPy is included together with Pandas for 7 days.
Pandas is commonly used in Python for working with tabular datasets, including data cleaning, filtering, transformation and analysis.
Yes. ETL is included for 7 days.
ETL stands for Extract, Transform and Load.
ETL helps move data from source systems, transform it into a useful format and load it into a target system for analytics or reporting.
Yes. Power BI is included for 3 days.
Power BI is used to create interactive reports, dashboards and visualizations from business data.
Yes. Snowflake is included for 15 days.
Snowflake provides cloud-based data platform capabilities that support scalable data warehousing and analytics workloads.
Yes. PySpark is included for 7 days.
PySpark introduces distributed data-processing concepts and is useful when working with larger datasets in big-data environments.
Yes. Linux is included for 5 days.
Linux skills are useful when working with servers, cloud environments, data platforms and command-line automation tools.
Yes. Cloud Storage is included for 5 days.
Pipeline modelling involves designing how data moves through different stages, from source and ingestion through transformation and delivery.
Yes. Pipeline Modelling is included for 5 days.
Yes. Schema Designs are included for 6 days.
Schema design helps organize data logically and efficiently for storage, querying and analytical reporting.
Yes. The course includes a dedicated 25-day capstone project.
Projects allow learners to apply programming, SQL, data processing, visualization and analytical concepts to practical datasets.
Yes. The program is designed for freshers who want to build foundational skills in Python, SQL, data analysis and modern data platforms.
Yes. BCA students interested in Python, databases and analytics can consider this program.
Yes. Engineering graduates can learn Data Analytics and develop skills across Python, SQL, BI and modern cloud data platforms.
Yes. MCA graduates can consider Data Analytics training as a strong pathway into data-related IT roles.
Yes. Beginners start with Python and SQL fundamentals before progressing to Pandas, ETL, BI, cloud and big-data technologies.
SQL is highly useful for working with relational and structured data and is an important skill for Data Analyst roles.
Python is essential, but Data Analyst roles often require a combination of SQL, data cleaning, analytics, visualization and business understanding.
Business intelligence and visualization tools like Power BI are valuable skills for reporting and communicating insights to stakeholders.
Data Analytics focuses on examining data to identify patterns and actionable insights. Data Science includes broader areas like predictive modeling and machine learning.
The syllabus focuses on Data Analytics technologies such as Python, SQL, Pandas, ETL, Power BI, Snowflake and PySpark.
Snowflake is a cloud-based data platform used for data storage, processing, data warehousing and analytics workloads.
PySpark is the Python interface for Apache Spark, used for large-scale distributed data processing.
Pandas is commonly used for local, in-memory tabular data analysis, while PySpark is designed for distributed processing across large datasets.
SQL is primarily used to query and manipulate data in databases, while Python is used for broader data processing, automation, analysis and library integration.
Important skills include SQL, Python, data cleaning, Pandas, visualization, analytical thinking and communication.
Python and SQL provide a strong foundation, supplemented by data-cleaning, visualization, analytical and problem-solving skills.
Yes. The syllabus includes Snowflake, schema design, ETL and pipeline modelling for modern data warehousing environments.
Yes. ETL, Snowflake, PySpark, cloud storage, pipeline modelling and schema design provide exposure to data engineering concepts.
No. Python is a major component, but the program also includes MySQL, NumPy, Pandas, ETL, Power BI, Snowflake, PySpark, Linux, cloud storage, pipeline modelling, schema design and a project.
The total course duration specified in the syllabus is 150 days.
The project is allocated 25 days.
Python is covered for 35 days.
MySQL is covered for 30 days.
Snowflake is covered for 15 days.
Power BI is covered for 3 days.
NumPy & Pandas are covered for 7 days.
PySpark is covered for 7 days.
ETL is covered for 7 days.
Yes. The program is presented as a Data Analytics with Python course and internship-oriented learning program at UNIQ Technologies.
The syllabus combines Python, SQL, analytics libraries, ETL, Power BI, Snowflake, PySpark, Linux, cloud storage, pipeline modelling, schema design and a dedicated 25-day project.