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Workshop detalis

Data Analytics

Workshop: 2/3days
MCAPG
Enrolled: 60 students
(30 Reviews)

Data Analytics is the process of examining, cleaning, transforming, and interpreting data to discover useful information, identify patterns, and support decision-making. It helps organizations understand past performance, predict future trends, and make data-driven decisions.

Data analytics uses tools and techniques such as Excel, SQL, Python, and data visualization tools to analyze structured and unstructured data. It involves data collection, data cleaning, exploratory data analysis (EDA), and statistical analysis to convert raw data into meaningful insights.

Course description

This course provides a comprehensive introduction to Data Analytics concepts, tools, and techniques used to analyze and interpret data for business and technical decision-making. Learners will gain practical skills in collecting, cleaning, and transforming data into meaningful insights using industry-standard tools.The course covers data analysis fundamentals, including Excel, SQL, and Python, along with Exploratory Data Analysis (EDA) and data visualization techniques.

What you'll learn from this course
  • Understanding the fundamentals of Data Analytics and its role in decision-making.
  • Learning data collection, cleaning, and preprocessing techniques.
  • Gaining hands-on experience with Excel, SQL, and Python for data analysis.
  • Performing Exploratory Data Analysis (EDA) to identify trends and patterns.
  • Creating data visualizations and dashboards to communicate insights clearly..
Certification

At TechIn IT, we proudly assure that every Trainee who successfully completes our program will be awarded a certificate. We are officially associated with APSCHE, AICTE, MSME, Skill India, IAF, and NASSCOM. The certification will reflect the Trainees dedication and skill development, recognized under national-level standards .

  • Introduction to Data Analytics

    Overview of Data Analytics and its importance.

    Types of data (structured and unstructured).

    Data Analytics lifecycle.

  • Data Cleaning and Analysis

    Data collection and data cleaning techniques.

    Handling missing values and duplicates.

    Exploratory Data Analysis (EDA).

  • Advanced Analytics and Visualization

    Introduction to SQL queries for data analysis.

    Data filtering, sorting, and aggregation.

    Advanced data visualization techniques.

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