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Certificate In Data Analytics with Python & AI(S-DAWP&A-8638)

  • Last updated Dec, 2025
  • Certified Course
₹24,000 ₹30,000
  • Duration5 Months
  • Enrolled0
  • Lectures150
  • Videos0
  • Notes0
  • CertificateYes

What you'll learn

About the Data Analytics Course

The Data Analytics Course is designed to equip learners with the essential skills required to collect, process, analyze, and visualize data to make informed business decisions. Whether you are a beginner or an experienced professional looking to upskill, this course provides a practical, industry-oriented learning experience.

What You Will Learn

  • Foundations of Data Analytics
  • Understanding data types, data structures, and the role of analytics in business.
  • Data Cleaning & Pre-processing
  • Techniques to prepare raw data for analysis using modern tools.
  • Exploratory Data Analysis (EDA)
  • Identifying patterns, trends, and insights using statistical methods.
  • Data Visualization
  • Creating impactful charts, dashboards, and reports using tools like Excel, Power BI, and Tableau.
  • Statistical Analysis & Predictive Modeling
  • Fundamentals of statistics, probability, regression, and forecasting.
  • Working with Databases
  • SQL queries, relational databases, and handling real datasets.
  • Python for Data Analysis
  • Using libraries like Pandas, NumPy, and Matplotlib for deeper insights.

Who This Course Is For

  • Students and beginners eager to enter the tech industry
  • Working professionals looking to switch or upskill
  • Business analysts, marketers, and managers
  • Anyone interested in data-driven decision making

Key Highlights

  • Hands-on learning with real-world datasets
  • Projects and case studies aligned with industry standards
  • Step-by-step guidance from expert trainers
  • Certificate of completion
  • Suitable for beginners — no prior coding experience required

Career Opportunities

After completing this course, learners can apply for roles such as:

  • Data Analyst
  • Business Analyst
  • MIS Analyst
  • Reporting Analyst
  • Junior Data Scientist
  • BI Developer








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Course Syllabus

Module 1: Introduction to Data Analytics

  • What is Data Analytics?
  • Types of Analytics: Descriptive, Diagnostic, Predictive & Prescriptive
  • Data lifecycle and Data ecosystem
  • Roles in Data Analytics
  • Real-world applications

Module 2: Excel for Data Analysis

  • Basic to Advanced Excel functions
  • Data cleaning & formatting
  • Lookup operations (VLOOKUP, XLOOKUP, INDEX-MATCH)
  • Pivot tables, Pivot charts
  • Conditional formatting
  • Dashboard creation

Module 3: SQL for Data Analytics

  • Introduction to Databases
  • SQL Basics (SELECT, WHERE, ORDER BY)
  • JOINs (INNER, LEFT, RIGHT, FULL)
  • GROUP BY, HAVING
  • Subqueries
  • Aggregate functions
  • Creating tables, inserting data
  • Real-world query writing

Module 4: Statistics & Probability

  • Types of Data
  • Measures of Central Tendency (Mean, Median, Mode)
  • Measures of Dispersion (Variance, SD)
  • Probability basics
  • Hypothesis Testing
  • Correlation & Regression
  • Outliers & Data distribution

Module 5: Python for Data Analysis

  • Python basics & environment setup
  • Working with Jupyter Notebook
  • Data types, variables, loops, functions
  • Libraries:
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Data cleaning with Pandas
  • Exploratory Data Analysis (EDA)
  • Plotting and Visualization

Module 6: Data Visualization Tools

Power BI

  • Power BI Interface
  • Importing & transforming data
  • DAX basics
  • Measures & Calculated Columns
  • Visualizations & Dashboards
  • Publishing & Sharing Reports

Tableau (optional/advanced)

  • Connecting to data sources
  • Calculated fields
  • Filters & Parameters
  • Dashboards & Stories

Module 7: Business Analytics & Domain Knowledge

  • Understanding business KPIs
  • How companies use data
  • Case studies:
  • Sales analytics
  • Customer analytics
  • Marketing analytics
  • Finance analytics

Module 8: Machine Learning (Beginner Level)

  • Introduction to machine learning
  • Data preprocessing
  • Linear Regression
  • Logistic Regression
  • Model evaluation (accuracy, precision, recall, F1 score)
  • Real-world prediction projects

Module 9: Visualization & Reporting

  • Building dashboards
  • Presenting insights
  • Report writing
  • Storytelling with data

Module 10: Projects & Assignments

  • Real-world datasets
  • End-to-end project:
  • Data collection
  • Cleaning
  • Analysis
  • Visualization
  • Final report
  • Resume preparation & interview questions


Course Fees

Course Fees
:
₹30000/-
Discounted Fees
:
₹ 24000/-
Course Duration
:
5 Months

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