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Data Analytics Internship

 

Kaashiv Infotech offers a comprehensive Data Analytics Internship tailored for students, providing practical exposure across domains such as business intelligence, data visualization, SQL, and machine learning. This internship emphasizes hands-on learning through real-world projects and advanced analytical tools, helping students bridge the gap between academics and the evolving data-driven industry.

With personalized mentorship from experienced professionals and access to top-notch resources, Kaashiv ensures that each intern develops job-ready skills and confidence to succeed in today’s competitive tech landscape.

Primary Objectives of the Data Analytics Internship

  • Enhance practical knowledge in data analytics using tools like Python, SQL, Excel, and Power BI.

  • Empower interns to work on real-world projects and derive insights from complex datasets.

  • Provide exposure to key areas such as data cleaning, visualization, dashboarding, and predictive modeling.

  • Help students align their skills with industry requirements and build a strong professional network.

  • Foster mentorship connections with industry experts, opening up potential career and collaborative opportunities.

Benefits of Doing a Data Analytics Internship at Kaashiv Infotech

  • Real-World Project Experience: Work with actual datasets and gain hands-on skills in data wrangling, analysis, and reporting.

  • Industry Mentorship: Learn directly from seasoned analysts and data professionals from companies like TCS, Wipro, HCL, and Zoho.

  • Career Readiness: Improve technical, analytical, and soft skills essential for roles such as Data Analyst, BI Developer, and Data Scientist.

  • Resume Enhancement: Stand out with certifications and a portfolio of completed projects.

  • Networking Opportunities: Build connections with mentors, peers, and industry experts.

  • Job Opportunities: Top performers may receive full-time job offers or referrals.

How to Prepare for the Data Analytics Internship

  • Strengthen fundamentals in Python, statistics, and basic SQL.

  • Familiarize yourself with data visualization tools such as Power BI or Excel.

  • Review Kaashiv Infotech’s focus areas and recent projects to align your interests and skills.

  • Be ready to learn collaboratively and communicate insights effectively.

Best Internship Opportunities at Kaashiv Infotech

Kaashiv Infotech delivers top-tier internship experiences in Data Analytics, Python, AI, Machine Learning, and Software Development. Their structured, hands-on learning model and dedicated mentorship make them one of the leading providers of tech internships in India.

5-Days Data Analytics Internship Program

Day 1: Introduction to Data Analytics and Python Basics

  • What is Data Analytics?

    • Types: Descriptive, Diagnostic, Predictive, Prescriptive

    • Applications in Business, Healthcare, Finance, and Marketing

  • Python Basics:

    • Variables, Data Types, Operators

    • Control Structures: Loops, If-else

    • Functions and List Comprehensions

Day 2: Data Handling with Pandas and Data Visualization

  • Pandas:

    • Reading CSV, Excel, JSON

    • Cleaning Data, Handling Missing Values

    • Sorting, Grouping, Filtering

  • Visualization with Matplotlib & Seaborn:

    • Line, Bar, and Scatter Plots

    • Histograms & Box Plots

Day 3: SQL for Data Analytics (Common with Cybersecurity & Networking)

  • CRUD Operations (SELECT, INSERT, UPDATE, DELETE)

  • Filtering with WHERE, GROUP BY, HAVING

  • JOINs: INNER, LEFT, RIGHT, FULL

  • Nested Queries

Day 4: Business Intelligence & Dashboarding

  • Power BI:

    • Intro to Power BI UI

    • Data Modeling & Creating Dashboards

  • Excel:

    • Pivot Tables & Charts

    • VLOOKUP, HLOOKUP, INDEX, MATCH

    • Power Query for Data Cleaning

Day 5: Final Project

  • Analyze a real-world dataset

  • Create dashboards in Power BI

  • Present insights and recommendations

10-Days Comprehensive Data Analytics Internship Program

Day 1: Python Fundamentals & Pandas Basics

  • Introduction to Python for Data Analysis
  • Variables, Data Types, Lists, Dictionaries, and Functions
  • Introduction to Jupyter Notebooks
  • Pandas DataFrames: Creating, Reading (CSV, Excel), Basic Operations
  • Data Selection, Filtering, Indexing

Day 2: Merging and Concatenating DataFrames

  • Merging DataFrames with merge() (Inner, Outer, Left, Right Joins)
  • Concatenating DataFrames with concat()
  • Use cases of merge vs. concat
  • Handling missing values during merging
  • Practice Exercises with real datasets

Day 3: Data Cleaning & EDA

  • Handling Outliers: IQR, Z-score methods
  • Removing Duplicates and Null Values
  • Feature Engineering: Extracting DateTime parts, Creating new features
  • Introduction to Exploratory Data Analysis (EDA)
  • Summary Statistics, Correlation Matrix

Day 4: Advanced SQL

  • SQL Joins and Subqueries Recap
  • Window Functions: ROW_NUMBER, RANK, NTILE
  • Conditional Aggregation using CASE WHEN
  • Common Table Expressions (CTEs)
  • Real-time SQL Problem Solving

Day 5: Power BI DAX and Dashboards

  • Introduction to Power BI
  • Key DAX Functions:
  • SUMX, CALCULATE, FILTER, RELATED
  • Data Modeling Concepts
  • Creating Interactive Dashboards
  • Dashboard Design Best Practices (color, layout, usability)

Day 6: Statistics for Data Analysis

  • Descriptive Statistics:
  • Mean, Median, Mode, Variance, Standard Deviation
  • Distributions and Normality Checks
  • Confidence Intervals
  • Hypothesis Testing: Z-test, T-test
  • A/B Testing Concept and Interpretation

Day 7: Machine Learning Introduction

  • ML Workflow Overview
  • Types of Machine Learning:
  • Supervised vs. Unsupervised
  • Scikit-learn Overview
  • Dataset Splitting: Train/Test
  • Introduction to Regression & Classification

Day 8: Regression Modeling

  • Linear Regression: Assumptions, Interpretation
  • Building a Linear Regression Model with scikit-learn
  • Model Evaluation Metrics: RMSE, MAE, R²
  • Feature Scaling: StandardScaler, MinMaxScaler
  • Residual Analysis

Day 9: Advanced Time Series & Automation

  • Time Series Components: Trend, Seasonality, Noise
  • Moving Averages, Exponential Smoothing
  • ARIMA, Prophet (basic intro)
  • Automating EDA and Reporting using Python (e.g., Jupyter Notebook → PDF/HTML)
  • Automating Email Reports with Python

Day 10: Final Project & Presentation

  • Work on Capstone Project:
  • Predictive Model (e.g., Sales Forecast, Churn Prediction) or
  • Interactive Dashboard (e.g., Power BI with DAX + SQL backend)
  • Prepare a Slide Deck with EDA, Model, and Business Insights
  • Final Presentations: 10–15 min per team
  • Q&A and Feedback

Registration Details

  • New Batches Start Daily – Choose any convenient date.

  • WhatsApp / Call: +91 7667663035

  • Online Registration: [Click here to register]

  • Certificates Provided:

Duration & Timings

  • Flexible duration: 6 Days to 6 Months

  • Daily Training: 3 Hours/Day

  • Open All 7 Days, including weekends and holidays

Trainers from Top MNCs

Professionals with experience in companies like:

  • HCL Technologies

  • TCS

  • Oracle

  • Zoho

  • Wipro

  • Cognizant

  • Cisco

📍 Address

Kaashiv Infotech
3A, 1st Cross Street, PH Road,
Near Shenbaga Bhavan Hotel & Opp. FB Cakes,
Maduravoyal, Chennai – 600095

📞 Contact Numbers

  • +91 7667663035

  • +91 7667662428

  • +91 9840678906

  • +91 9962066262

📧 Email: kaashiv.info@gmail.com

 

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