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Data Analytics Course in Pune

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📌 Objective: Understand the fundamentals of data analytics and its importance in decision-making.

  • What is Data Analytics?
  • Role of a Data Analyst in different industries
  • Understanding Data Types & Data Sources
  • Data vs. Information vs. Insights
  • Overview of ETL (Extract, Transform, Load) Process
  • Tools used in Data Analytics (Excel, SQL, Python, Tableau, Power BI)
  • Career opportunities in Data Analytics

📝 Hands-on Exercise: Identifying and classifying different types of data.

 

📌 Objective: Use Microsoft Excel for data cleaning, analysis, and visualization.

  • Basic & Advanced Excel Functions
    • SUM(), COUNT(), IF(), VLOOKUP(), HLOOKUP()
    • INDEX-MATCH(), XLOOKUP(), TEXT(), DATE(), IFERROR()
  • Data Cleaning Techniques
    • Removing duplicates, handling missing values
    • Using Text-to-Columns, Flash Fill
  • Pivot Tables & Pivot Charts
  • Conditional Formatting & Data Validation
  • Introduction to Excel Dashboards

📝 Hands-on Exercise: Creating a Sales Performance Dashboard using Pivot Tables & Charts.

📌 Objective: Learn SQL for querying and managing structured databases.

  • Introduction to Databases & SQL
  • Understanding Database Management Systems (DBMS)
  • SQL Queries:
    • SELECT, WHERE, ORDER BY, GROUP BY, HAVING
    • JOIN operations (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN)
    • Subqueries & Common Table Expressions (CTEs)
  • Data Aggregation & Manipulation:
    • Using COUNT(), SUM(), AVG(), MAX(), MIN()
    • Window Functions (ROW_NUMBER(), RANK(), DENSE_RANK())
  • Optimizing Queries for Large Datasets

📝 Hands-on Exercise: Writing SQL queries to analyze a customer database.

📌 Objective: Use Python for data manipulation, analysis, and visualization.

  • Introduction to Python & Jupyter Notebook
  • Python Libraries for Data Analysis:
    • pandas (Data Manipulation)
    • numpy (Mathematical Computation)
    • matplotlib & seaborn (Data Visualization)
  • Data Cleaning in Python
  • Working with CSV & Excel files in Python
  • Exploratory Data Analysis (EDA)

📝 Hands-on Exercise: Analyzing a dataset using Python (pandas, matplotlib, seaborn).

📌 Objective: Learn how to create interactive dashboards and reports.

Tableau Basics

  • Understanding Tableau Interface & Connecting to Data Sources
  • Creating Bar Charts, Line Graphs, Pie Charts
  • Filters, Groups, and Parameters
  • Creating Interactive Dashboards
  • Using Calculated Fields & Trend Analysis

Power BI Basics

  • Introduction to Power BI Desktop & Power Query
  • Importing and Transforming Data
  • Creating DAX (Data Analysis Expressions) Measures
  • Building Interactive Reports & Dashboards

📝 Hands-on Exercise: Creating a Business Performance Dashboard in Tableau/Power BI.

📌 Objective: Apply statistical methods for better data-driven decision-making.

  • Understanding Descriptive & Inferential Statistics
  • Mean, Median, Mode, Standard Deviation, Variance
  • Hypothesis Testing (T-test, Chi-square test)
  • Correlation & Regression Analysis
  • A/B Testing & Real-world Case Studies

📝 Hands-on Exercise: Running statistical tests on customer satisfaction data.

Module 7: Machine Learning for Data Analysts (Optional)

📌 Objective: Learn basic machine learning concepts and predictive modeling.

  • Introduction to Machine Learning & its applications
  • Supervised vs. Unsupervised Learning
  • Understanding Regression & Classification Models
  • Using scikit-learn in Python for predictive analysis
  • Implementing Linear Regression & Decision Trees
  • Evaluating model performance

📝 Hands-on Exercise: Building a simple Predictive Model for Sales Forecasting.

📌 Objective: Understand real-world business applications of data analytics.

  • How businesses use Data Analytics for decision-making
  • Industry-Specific Case Studies:
    • Retail Analytics – Sales trends & customer insights
    • Finance Analytics – Fraud detection & risk analysis
    • Healthcare Analytics – Patient data insights
  • Best Practices for Data-Driven Decision Making

📝 Hands-on Exercise: Solving a real-world business problem using data analytics tools.

📌 Objective: Apply all concepts learned in a final end-to-end project.

  • Choose a business problem (e.g., customer churn, sales forecasting, fraud detection)
  • Work with real-world datasets
  • Perform data cleaning, visualization, and analysis
  • Create an interactive dashboard
  • Present findings in a professional report

Frequently Asked Questions

The Data Analytics course at Skyline Institute typically lasts between 10 to 12 weeks, depending on the batch type (regular or fast-track). Each session is around 1.5 to 2 hours, with hands-on practice and assignments. We offer both classroom (offline) and online training, ensuring flexibility for students and working professionals. Weekend batches are also available for those who cannot attend weekday classes. Our courses are structured to be job-oriented, ensuring students get practical experience along with theoretical knowledge. Students also receive recorded sessions and study materials for revision.

No prior coding experience is required to enroll in this course. The Data Analytics course is designed for absolute beginners as well as professionals looking to upskill. Basic knowledge of Excel and statistics is helpful but not mandatory. We start with the fundamentals of data handling before progressing to advanced topics like SQL, Python, and Power BI. The course is structured to help students from non-technical backgrounds become proficient in data analysis. Our expert trainers ensure that students understand concepts step-by-step, making it easy to follow even for beginners.

The course covers everything from basic to advanced data analytics skills. Key topics include:
✔ Excel for Data Analysis – Pivot tables, formulas, and dashboards
✔ SQL for Data Extraction – Writing queries, joins, and data manipulation
✔ Python for Data Analysis – Pandas, NumPy, and Matplotlib for visualization
✔ Statistics for Data Analysis – Mean, median, regression, and hypothesis testing
✔ Power BI & Tableau – Creating interactive dashboards
✔ Business Intelligence & Case Studies – Real-world applications of data analytics
✔ Capstone Project – Applying all concepts to a real-world business problem
This course is designed to equip students with hands-on experience, making them industry-ready.

Data Analytics is one of the fastest-growing fields, with high demand across multiple industries. After completing this course, students can apply for roles such as:

  • Data Analyst
  • Business Intelligence Analyst
  • SQL/Data Reporting Analyst
  • Market Research Analyst
  • Financial Analyst
    Companies across industries like IT, Finance, Healthcare, E-commerce, and Marketing hire data analysts to help them make data-driven decisions. Many of our past students have successfully transitioned into high-paying jobs in reputed companies after completing this course.

Yes, Skyline Institute provides comprehensive placement support to help students secure jobs. We offer:
✅ Resume Building & LinkedIn Profile Optimization
✅ Mock Interviews & Technical Tests
✅ Guidance on Job Portals & Networking Strategies
✅ Referrals to Companies Hiring Data Analysts
Our industry connections and dedicated placement cell ensure that students get access to relevant job opportunities. Many of our students have secured jobs in MNCs, startups, and analytics firms after completing the course.

After successfully completing the course, students will receive a Certificate of Completion from Skyline Institute. This certificate can be added to resumes and LinkedIn profiles, increasing job prospects. We also provide guidance for internationally recognized certifications such as:
✔ Microsoft Excel Certification (MOS)
✔ Tableau Desktop Specialist Certification
✔ Google Data Analytics Certification
✔ Power BI Certification
Earning these certifications can significantly boost a candidate’s credibility and career opportunities.

This course is designed to be highly practical, ensuring that students learn by doing. Every module includes hands-on exercises, case studies, and real-world projects. Students will work on datasets related to sales, marketing, finance, healthcare, and e-commerce. The final capstone project involves analyzing a real-world business problem, applying all learned concepts, and presenting insights using Power BI/Tableau dashboards. These projects can be showcased in job interviews, helping students stand out to employers.

Yes, we understand that students may sometimes miss a class due to other commitments. For this reason, all enrolled students get access to recorded sessions, which can be watched at their convenience. Additionally, we offer doubt-clearing sessions, where trainers provide extra support to students who need help with specific topics. We also provide PDF notes, practice exercises, and sample datasets to ensure that students can catch up easily.

The course fee varies based on the batch type (regular, fast-track, weekend) and training mode (offline or online). Skyline Institute offers affordable pricing with flexible payment options. We also provide:
✔ Early bird discounts for students who enroll early
✔ Group discounts for teams or friends enrolling together
✔ Referral offers for students who refer others
✔ EMI options for those who need financial flexibility
Students or parents can contact our admission team for detailed pricing and current offers.

Skyline Institute is one of the leading training institutes in Pune, known for providing high-quality training with job-oriented skills. Here’s why students choose us:
✅ Industry-Relevant Curriculum – Designed by experts working in top companies
✅ Practical Learning Approach – Real-world case studies & hands-on projects
✅ Expert Trainers – Instructors with 8+ years of industry experience
✅ Placement Assistance – Helping students get hired in top companies
✅ Flexible Learning Options – Both classroom & online training available
Our training ensures that students not only gain theoretical knowledge but also develop the practical skills required for real-world data analytics jobs.