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Course Highlights

  • Intensive Data Science training in Hyderabad, featuring Python, SQL, Statistics, Machine Learning (ML), and BI tools; delivered through instructor-led sessions and real-time projects, with authorised certification and placement support. ​
  • Includes 300+ hours of guided learning, self‑paced videos, lifetime access, 24/7 support, and flexible schedules designed for beginners and IT professionals to build a job‑ready portfolio.

  • Skill Type

  • Course Duration

  • Domain

  • GOI Incentive applicable

  • Course Category

  • Nasscom Assessment

  • Placement Assistance

  • Certificate Earned

  • Content Alignment Type

  • NOS Details

  • Mode of Delivery

Course Details

Learning Objectives

What will you learn in the Data Science Course?

  • Apply Python, SQL, and Statistics to clean, analyse, and visualise data for business insights. ​
  • Build, evaluate, and tune supervised and unsupervised ML models and deploy simple apps. ​
  • Create interactive dashboards in Power BI/Tableau and communicate results with industry best practices.
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Reasons to enrol

Why should you take the Data Science Course?

  • Structured curriculum with expert mentors, real-world projects, and authorised certification to become job-ready ​
  • 300+ hours guided training with lifetime access, flexible batches, and 24/7 support
  • Placement assistance with a large hiring network to accelerate entry into data roles
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Ideal Participants

Who should take the Data Science Course?

  • Students, freshers, and career switchers seeking entry-level data roles ​
  • Working professionals in IT, analytics, or related domains upskilling to Data Science ​
  • Entrepreneurs and business teams wanting data-driven decision-making skills
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Curriculum

Curriculum

  • Foundations: Python, NumPy, Pandas, Visualisation (Matplotlib, Seaborn, Plotly), SQL, Excel ​
  • Statistics and EDA: Descriptive and inferential stats, probability, hypothesis testing, data cleaning ​
  • ML: Regression, classification, clustering, dimensionality reduction, model tuning, and evaluation​
  • Advanced/NLP/Deep Learning basics with practical mini-projects and deployment using Flask/Streamlit
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skills and tools

Tools you will learn in Data Science Course

  • Python
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Plotly
  • SQL/MySQL
  • Excel
  • Power BI
  • Tableau
  • Scikit‑learn
  • Flask/Streamlit
  • Basic AWS/PythonAnywhere Deployment Workflows
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