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Unlock Your Potential with Industry-Recognized Data Analytics Certification

In today’s data-driven world, organizations rely on skilled data analysts to transform raw data into actionable insights. Our Data Analytics Certification from Techtroma is designed to equip professionals with the analytical, statistical, and technical skills required to excel in this dynamic field. 

Why Choose This Certification?

  • Industry-Recognized Certification – Gain a competitive edge with a globally accepted credential from Techtroma.
  • Hands-On Learning – Work on real-world datasets, case studies, and industry projects.
  • Expert-Led Training – Learn from seasoned data analysts and industry practitioners.
  • Flexible Learning Modes – Online, classroom, and hybrid options to suit your schedule.
  • Placement Assistance – Get career guidance and job support after certification.

What You Will Learn?

Data Analytics Foundations

Understanding data types, data structures & preprocessing.

Statistical Analysis

Descriptive & inferential statistics, hypothesis testing

SQL for Data Analysis

Writing queries, data extraction & transformation.

Data Visualization

Using Power BI, Tableau, and Excel to present insights.

Machine Learning Basics

Introduction to predictive analytics and clustering techniques.

Python for Data Analytics

Hands-on coding with NumPy, Pandas, and Matplotlib.

Real-World Case Studies

Practical exposure to business use cases across industries.

Who Can Enroll?

  • Aspiring Data Analysts & Business Analysts
  • Professionals from IT, Marketing, Finance, and Operations
  • Students and Freshers looking to enter the analytics domain
  • Entrepreneurs & Business Owners seeking data-driven strategies

Course Curriculum

Module 1: Introduction to Data Analytics
  • Introduction to Data Analyst 
  • What is Data Analyst? 
  • Why Data Analyst? 
  • Cases for Data Analyst. 
  • 1.5 Data Analyst Classification.
Module 2: Basic Python Programming
  • Introduction 
  • Python Data Types- int, Number, Boolean 
  • String, Tuple, List, Dictionary, & set. 
  • String Operations and Functions. 
  • Tuple operation and Functions.
  • List operation and Functions 
  • Set operation & Functions. 
  • Dictionary operation & Functions.
  • If-else, elif Statement 
  • Loops & Break & Continue Statement.
Module 3: Basic Statistics
  • Introduction to Statistics. 
  • Data Types. 
  • Central tendency. 
  • Dispersion.
Module 4: Data Visualization
  • Basic Statistics Contents. 
  • Datasets. 
  • Graph designing. 
  • Filtering dataset
  • Mapping a dataset
Module 5: Business Analytics using Excel
  • Basics of Business Analytics. 
  • Excel Conditional Formatting & Key Functions. 
  • Data Analysis with Pivot Tables. 
  • Creating Dashboards. 
  • Advanced Business Analytics Using Excel.
Module 6: Advanced Excel
  • Writing conditional expressions (using IF). 
  • Sorting and Filtering Data. 
  • Data Validations. 
  • Creating Pivot tables. 
  • Date and time functions.
Module 7: SQL Fundamentals

Essential SQL Statements. 

Database Backup & Restore Techniques.

Data Selection & Filtering. 

Data Selection & Ordering 

Advanced SQL Topics.

Module 8: Power BI

Introduction to Power BI. 

Creating and managing interactive reports and dashboards. 

Utilizing advanced features like Quick Insights and natural language queries. 

Best practices for data layout, visualization, and collaboration using Microsoft Teams. 

Example of Power BI.

Module 9: Tableu
  • Introduction Tableau. 
  • Introduction to tableau and its core concepts. 
  • Creating various types of visualizations, including charts and graphs. 
  • Building interactive tableau dashboards & visual stories 
  • Data blending & formatting techniques for effective visualization. 
  • Examples.
Module 10: Advanced Data Visualization

Slicers & Filters in Power BI 

Interactive Visualizations in Power BI 

Creating Dashboards in Power BI

Module 11: Data Cleaning & Transformation using Excel
  • Data Cleaning Techniques 
  • Data Transform Techniques
  • Inbuilt Column and Row Transformations
Module 12: Power Query
  • Introduction to Power Query 
  • Data Types & Filters in Power Query. 
  • Creating a Query in Power Query
Module 13: Publishing Dashboards
  • Introduction to Power BI Service 
  • Introduction of Dashboards. 
  • Collaboration using Power BI 
  • Creating Dashboards using Power BI Cloud/Service. 
  • Publishing Your Dashboard

Data Analyst Project Life Cycle

Phase 1:Data Preparation Phase

This phase involves understanding business objectives, collecting data from various sources, and cleaning it to ensure accuracy. Exploratory Data Analysis (EDA) is conducted to identify patterns, trends, and anomalies, helping shape the analysis approach.

Phase 2:Data Analysis & Modeling Phase

Data is transformed and analyzed using statistical techniques, machine learning models, or business intelligence tools. Insights are derived through regression, clustering, or predictive modeling, ensuring alignment with business goals and validating hypotheses.

Phase 3:Interpretation & Reporting Phase

Findings are visualized using dashboards and reports to communicate insights effectively. Actionable recommendations are provided, followed by implementation and continuous monitoring to optimize strategies and ensure data-driven decision-making.

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