Data Analytics

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About Course

Data Analytics (Online Live Interaction Classes)

Internship with Live Projects

Welcome to our Comprehensive Data Analytics Bootcamp, a power-packed learning experience designed to equip you with the skills and techniques essential for thriving in the field of data analytics. Whether you’re a beginner or looking to enhance your existing skills, this bootcamp is tailored to cater to a diverse audience.

  1. Hands-On Learning: Immerse yourself in practical, hands-on exercises and real-world case studies to gain a thorough understanding of data analytics concepts.
  2. Expert-Led Instruction: Learn from industry experts who bring real-world experience and insights to the classroom, providing valuable perspectives on the application of data analytics in various domains.
  3. Project-Based Approach: Apply your skills to meaningful projects that simulate the challenges faced in the industry, building a robust portfolio to showcase to potential employers.
  4. Career-Ready Skills: Acquire the skills that employers are actively seeking, making you well-prepared for a successful career in data analytics.

    Classes Duration

    • Weekend Session Duration ( 2 Months) 2 Sessions Per Week of 2 Hours 
    • Weekday Session Schedule ( 1 Months ) 4 Sessions Per Week of 2 Hours
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What Will You Learn?

  • Introduction to Data Analytics:
  • Understand the role of data analytics in business and decision-making.
  • Explore the key concepts and terminology used in the field.
  • Data Collection and Cleaning:
  • Learn effective methods for collecting, cleaning, and organizing data.
  • Understand data quality and the importance of ensuring accurate and reliable datasets.
  • Exploratory Data Analysis (EDA):
  • Utilize statistical and visual methods to explore and understand data patterns.
  • Develop skills in data visualization to communicate insights effectively.
  • Statistical Foundations:
  • Gain a solid understanding of fundamental statistical concepts used in data analytics.
  • Apply statistical techniques to make data-driven decisions.
  • Introduction to Data Visualization Tools:
  • Explore popular data visualization tools such as Tableau and Matplotlib.
  • Create compelling visualizations to convey complex information in a clear and concise manner.
  • Descriptive and Inferential Statistics:
  • Dive into descriptive statistics to summarize and describe key features of data.
  • Understand inferential statistics for drawing conclusions and making predictions.
  • Introduction to Predictive Analytics:
  • Explore predictive modeling techniques to forecast future trends.
  • Understand the principles of regression analysis and time series forecasting.
  • Practical Applications and Case Studies:
  • Apply data analytics techniques to real-world scenarios through hands-on projects.
  • Analyze case studies to gain practical insights into industry-specific applications.

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