Data Analytics - Techpragna
Data Analytics Training Unlock data potential with hands-on analytics projects using real-world datasets Master essential tools: Excel, SQL, Python, Power BI, Tableau, and Statistics Live online and offline interactive sessions from top industry professionals Guaranteed placement support through our career advancement services Understand data wrangling, visualization, reporting, and business intelligence Download Curriculum Talk to Our Advisor Data Analytics Training Unlock data potential with hands-on analytics projects using real-world datasets Master essential tools: Excel, SQL, Python, Power BI, Tableau, and Statistics Live online and offline interactive sessions from top industry professionals Guaranteed placement support through our career advancement services Understand data wrangling, visualization, reporting, and business intelligence Download Curriculum Talk to Our Advisor World-Class Instructors 1:1 with Industry Mentors 55% Avg. Salary Hike Interview Preparation World-Class Instructors 1:1 with Industry Mentors 55% Avg. Salary Hike Interview Preparation What You’ll Learn Accelerate your career in data with our Data Analytics Training at TechPragna in Bangalore. This comprehensive course equips you with the tools and techniques to collect, analyze, and visualize data for actionable business insights—perfect for both beginners and working professionals. Data Analytics Training – Key Features Master essential tools: Excel, SQL, Python, Power BI, Tableau, and Statistics Live online and offline interactive sessions from top industry professionals Guaranteed placement support through our career advancement services Master essential tools: Excel, SQL, Python, Power BI, Tableau, and Statistics Live online and offline interactive sessions from top industry professionals Guaranteed placement support through our career advancement services Request more information Please enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form. Name * FirstLast Numbers *Email *DropdownSelect CourseData AnalyticsSoftware TestingFull Stack TrainingData ScienceNetwork EngineerDevOps CourseCloud ComputingParagraph Text Submit What You’ll Learn Accelerate your career in data with our Data Analytics Training at TechPragna in Bangalore. This comprehensive course equips you with the tools and techniques to collect, analyze, and visualize data for actionable business insights—perfect for both beginners and working professionals. Data Analytics Training – Key Features Master essential tools: Excel, SQL, Python, Power BI, Tableau, and Statistics Live online and offline interactive sessions from top industry professionals Guaranteed placement support through our career advancement services Master essential tools: Excel, SQL, Python, Power BI, Tableau, and Statistics Live online and offline interactive sessions from top industry professionals Guaranteed placement support through our career advancement services Request more information Please enable JavaScript in your browser to complete this form.Please enable JavaScript in your browser to complete this form. Name * FirstLast Numbers *Email *DropdownSelect CourseData AnalyticsSoftware TestingFull Stack TrainingData ScienceNetwork EngineerDevOps CourseCloud ComputingParagraph Text Submit Data Analytics Course Curriculum Data Analytics Course Curriculum Introduction to Data Analytics What is Data Analytics? Importance of Data-Driven Decision Making Types of Data Analytics: Descriptive, Diagnostic, Predictive, Prescriptive Key Roles in Data Analytics Data Analytics Lifecycle Real-World Applications of Data Analytics Career Scope and Opportunities Essential Tools and Technologies Overview Understanding Data and Data Types Structured vs Unstructured Data Quantitative vs Qualitative Data Data Sources in Modern Businesses Primary and Secondary Data Collection Methods Importance of Data Cleaning Data Privacy and Security Fundamentals Identifying Biases in Data Best Practices in Data Collection and Storage Data Collection Techniques Structured vs Unstructured Data Quantitative vs Qualitative Data Data Sources in Modern Businesses Primary and Secondary Data Collection Methods Importance of Data Cleaning Data Privacy and Security Fundamentals Identifying Biases in Data Best Practices in Data Collection and Storage Data Cleaning and Preparation Handling Missing Data Techniques Removing Duplicates and Errors Data Transformation and Normalization Data Encoding Methods (Label Encoding, One-Hot Encoding) Outlier Detection and Treatment Data Scaling Techniques (MinMax, StandardScaler) Data Integration from Multiple Sources Preparing Data for Analysis and Modeling Data Visualization Essentials Importance of Data Visualization Introduction to Visualization Tools (Tableau, Power BI, Python) Choosing the Right Chart Types Designing Effective Dashboards Best Practices for Storytelling with Data Interactive vs Static Visualizations Avoiding Misleading Visuals Hands-on Data Visualization Projects Statistical Fundamentals for Data Analytics Descriptive Statistics Overview Mean, Median, Mode, Variance, Standard Deviation Probability Basics Inferential Statistics Introduction Hypothesis Testing Concepts Correlation vs Causation Linear and Logistic Regression Basics Using Statistics in Business Analytics Excel for Data Analytics Advanced Excel Functions (VLOOKUP, INDEX, MATCH) Pivot Tables and Pivot Charts Data Cleaning in Excel Conditional Formatting Techniques Dashboard Creation in Excel Excel Macros and Automation Data Analysis ToolPak Usage Real-Life Data Projects with Excel SQL for Data Analytics SQL Basics: SELECT, WHERE, GROUP BY Data Filtering and Sorting JOINs (INNER, LEFT, RIGHT, FULL) Subqueries and Nested Queries Window Functions and Ranking Data Aggregation Techniques Data Manipulation (INSERT, UPDATE, DELETE) Hands-on SQL Practice with Real Data Python for Data Analytics Introduction to Python Programming Data Structures: Lists, Tuples, Dictionaries Data Manipulation with Pandas Data Visualization with Matplotlib & Seaborn Exploratory Data Analysis (EDA) Introduction to NumPy for Data Calculations Data Cleaning with Python Project: Analyzing Business Data using Python Introduction to Machine Learning Basics of Machine Learning Supervised vs Unsupervised Learning Regression Techniques Classification Algorithms Clustering Fundamentals Model Evaluation Metrics (Accuracy, F1 Score) Overfitting and Underfitting Concepts Practical Mini-Projects using ML Power BI for Business Analytics Power BI Interface and Navigation Connecting Data Sources in Power BI Data Transformation with Power Query Building Interactive Reports DAX Basics for Calculations Sharing and Publishing Reports Custom Visuals and Marketplace Live Business Dashboard Project Capstone Project and Career Preparation Industry-Specific Data Analytics Project Applying End-to-End Data Analytics Lifecycle Resume Building for Data Analyst Roles Crafting an Impressive Data Portfolio Mock Interviews and Q&A Sessions LinkedIn Optimization for Data Analytics Interview Preparation and Case Studies Final Project Presentation and Feedback What is Data Analytics? Importance of Data-Driven Decision Making Types of Data Analytics: Descriptive, Diagnostic, Predictive, Prescriptive Key Roles in Data Analytics Data Analytics Lifecycle Real-World Applications of Data Analytics Career Scope and Opportunities Essential Tools and Technologies Overview Structured vs Unstructured Data Quantitative vs Qualitative Data Data Sources in Modern Businesses Primary and Secondary Data Collection Methods Importance of Data Cleaning Data Privacy and Security Fundamentals Identifying Biases in Data Best Practices in Data Collection
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