Data Science: Unlock Insights and Drive Decisions with Data

Learn how to extract valuable insights from data, build predictive models, and apply advanced analytical techniques to make informed business decisions. This course covers the entire data science pipeline, from data collection to model deployment.

Data science is transforming industries worldwide, helping businesses leverage data to drive decisions, improve operations, and predict future trends. Whether you’re looking to start a career in data science, transition from another field, or enhance your analytical skills, this course will provide you with the knowledge and practical experience to succeed. You’ll learn how to work with real-world datasets, clean and preprocess data, explore statistical analysis, and use machine learning algorithms to build predictive models.

What you’ll learn

  • Understand the foundational concepts of data science, including data collection, cleaning, and exploration.
  • Master statistical analysis techniques to derive insights from data.
  • Build and evaluate machine learning models for prediction and classification.
  • Learn how to visualize data to communicate insights effectively.
  • Work with popular data science libraries like Pandas, NumPy, Matplotlib, Scikit-learn, and more.
  • Understand how to deploy data science models to make predictions in real-world applications.

Course Curriculum

Understand what data science is and how it’s used to solve real-world problems.

Learn how to gather data from various sources and clean it to ensure it’s ready for analysis.

Explore data using statistical techniques to uncover hidden patterns and relationships.

Master the statistical methods used to summarize and analyze data, including hypothesis testing.

Learn how to create compelling visualizations to communicate your findings effectively using libraries like Matplotlib and Seaborn.

Get an overview of machine learning and learn how to implement algorithms like linear regression, decision trees, and k-nearest neighbors (KNN).

Dive deeper into regression and classification algorithms, and understand how to evaluate model performance.

Explore clustering and dimensionality reduction methods like K-means and PCA.

Understand the basics of neural networks and how they are used to solve complex problems.

Learn how to deploy models and integrate them into production systems.


Course Materials Provided

  • In-Depth Video Lessons: Clear and structured tutorials that guide you through each data science concept and technique.
  • Hands-On Projects: Real-life case studies that allow you to apply your learning to practical problems.
  • Access to Resources: Downloadable scripts, code samples, and datasets to assist with your learning.
  • Knowledge Checks: Engaging assessments to test your comprehension and reinforce key concepts.
  • Industry Expert Insights: Learn from seasoned professionals who share their experience and tips for success in data science.

Who this course is for

  • Beginners: Individuals with no prior experience who want to explore a new field and build foundational knowledge from scratch.
  • Students: College or school learners aiming to gain skills that enhance their academic profile and support their career goals.
  • Professionals: Working individuals such as engineers, analysts, developers, or managers looking to upskill or transition into data science roles.
  • Tech Enthusiasts: Passionate learners who enjoy exploring emerging technologies and want hands-on experience with data-driven insights.

Course Details

Key Takeaways

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    Pricing

    Prices that are budget-friendly and suitable for students.

    Core Learning

    Build strong fundamentals with self-paced sessions.

    ₹ 5500 + 18% GST

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    Premium Led Learning

    Level up with expert-guided training and live sessions.

    ₹ 7500 + 18% GST

    Advanced

    Master the skillset with hands-on projects and job-focused training.

    ₹ 10,000 + 18% GST

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