Description

Course  Description:

The Data Analytics is the process of examining data sets to find trends and draw conclusions about the information they contain. It involves analyzing raw data, collecting and cleaning it, and transforming it into actionable insights. These insights can be used to support decision-making, improve business operations, and gain a competitive advantage.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities after Data analytics: 

• Data Analyst
• Business Analyst
• Data Scientist
• Data Engineer
• Marketing Analyst
• Financial Analyst
• Operations Analyst
• Product Analyst

Essential Skils you will Develop Data analytics: 

• Data Analysis & Interpretation
• Programming & Tools
• Data Visualization
• Data Cleaning & Preparation
• Statistical Thinking
• Critical Thinking & Problem Solving

Tools Covered:

• Spreadsheet Tools
• Microsoft Excel – Data cleaning, basic analysis, pivot tables, dashboards
• Google Sheets – Online data collaboration and analysis
• Programming Languages
• Python – Data wrangling, analysis, and visualization (libraries: Pandas, NumPy, Matplotlib, Seaborn)
• R – Statistical analysis and data visualization (ggplot2, dplyr, tidyr)
• Database Management
• SQL – Querying and managing structured data
• MySQL / PostgreSQL – Popular relational database systems

Syllabus:

Module 1: Introduction to Data Analytics What is Data Analytics? Types of Analytics: Descriptive, Diagnostic, Predictive, Prescriptive Data Lifecycle and Analytics Pipeline
Applications across Industries Roles: Data Analyst vs Data Scientist vs Data Engineer.

Module 2: Excel for Data Analysis Excel Basics: Formulas, Functions, and Formatting Lookup Functions (VLOOKUP, HLOOKUP, INDEX-MATCH) Pivot Tables and Charts Data Cleaning in Excel Dashboards using Excel.

Module 3: Statistics and Probability for Data Analytics Mean, Median, Mode, Variance, Standard Deviation Probability Distributions Hypothesis Testing (Z-test, T-test, Chi-square) Correlation vs Causation Inferential vs Descriptive Statistics.

Module 4: SQL for Data Analytics Introduction to Databases SELECT, WHERE, GROUP BY, HAVING, ORDER BY JOINs: INNER, LEFT, RIGHT, FULL Subqueries and CTEs Aggregation and Window Functions.

Module 5: Data Visualization Tools (Tableau / Power BI) Introduction to BI Tools
Data Import and Transformation Creating Dashboards and Reports Charts: Bar, Line, Pie, Maps, TreeMaps Storytelling with Data.

Module 6: Python for Data Analysis Python Basics: Variables, Lists, Dictionaries, Loops, Functions Libraries: NumPy, Pandas Data Cleaning and Manipulation with Pandas Handling Missing Data and Outliers File Handling CSV, Excel, JSON.

Module 7: Data Wrangling & EDA Exploratory Data Analysis Data Collection and Inspection Removing Duplicates and Nulls Feature Engineering & Transformation
Univariate & Bivariate Analysis Visualization using Seaborn & Matplotlib.

Module 8: Introduction to Machine Learning Supervised vs Unsupervised Learning
Regression and Classification Basics Model Building using Scikit-Learn Train-Test Split, Cross Validation Model Evaluation Metrics Accuracy, F1, ROC.

Module 9: Data Analytics in Real Business Use Cases Sales Analysis Customer Retention Supply Chain Optimization Marketing Campaign Effectiveness Finance Forecasting & Reporting.

Module 10: Capstone Project & Career Preparation Real-World Project (from dataset to dashboard) Final Report Submission & Presentation Resume Building & Portfolio Setup Interview Questions for Data Analyst Role Freelance & Job Market Guidance.

Industry Projects:

• Retail & E-Commerce
• Finance & Banking
• Healthcare
• Manufacturing
• Marketing & Media
• Transportation & Logistics

Who is this program for?

• Beginners and Fresh Graduates
• Working Professionals
• Career Switchers
• Entrepreneurs & Business Owners
• Students in STEM Fields
• Managers and Team Leads

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com