Web D School Online

Data Science
Course

A complete course that covers all of the
basics tothe advanced level.

Online Certification

Online Data Science Course

  1. Comprehensive Curriculum: Covers essential topics like data analysis, machine learning, statistics, Python programming, and data visualization.
  2. Hands-on Projects: Includes real-world datasets and practical applications to build your portfolio and enhance your skills.
  3. Flexible Learning: Offers self-paced learning with online resources, video lectures, and quizzes, allowing students to learn at their own convenience.
 
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Why Learn Online Data Science Course at Web D School?

  1. Expert Instructors: Learn from industry professionals with hands-on experience in data science, ensuring up-to-date knowledge and real-world insights.
  2. Practical Approach: Gain hands-on experience through projects, case studies, and data-driven challenges, preparing you for real-world data science roles.
  3. Flexible Learning: Access interactive lessons and resources online, allowing you to learn at your own pace, anytime and anywhere.
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Expansive Concepts

Online Data Science Course Syllabus

Extra Topics for a Deeper Understanding and Skill Enhancement

Data Science Courses Syllabus

  • NumPy: Arrays, mathematical operations, and linear algebra.
  • Pandas: DataFrames, Series, data manipulation, and cleaning.
  • Matplotlib and Seaborn: Data visualization techniques (basic charts, histograms, scatter plots, etc.).
    • Handling missing values.
    • Removing duplicates.
    • Data transformation (normalization, standardization).
    • Feature engineering and creation.
  • Matplotlib: Basic plotting, customizing plots, multiple subplots.
  • Seaborn: Statistical visualizations (heatmaps, box plots, pair plots).
  • Advanced Visualization: Plotly for interactive visualizations.
  • Data Storytelling: How to communicate insights effectively using visualizations.
  • Hypothesis testing (t-tests, chi-square tests, ANOVA).
  • Confidence intervals.
  • p-values and statistical significance.
  • Linear regression.
  • Multiple regression.
  • Evaluating regression models (R-squared, MSE, RMSE).

Why Web D School?

What You Should Know Before Starting Our Data Science Online Program

Data science

Data Science uses statistical analysis, machine learning, and programming to extract insights from data. It enables data-driven decision-making across various industries through predictive models and data visualization.

Data analyst

A Data Analyst collects, processes, and analyzes data to help organizations make informed decisions. They use tools like Excel, SQL, and data visualization software to identify trends and patterns in business data.

Data analyst

A Data Analyst collects, processes, and analyzes data to help organizations make informed decisions. They use tools like Excel, SQL, and data visualization software to identify trends and patterns in business data.

Python

Python is a versatile, high-level programming language used for web development, data analysis, automation, and artificial intelligence. Its simplicity and powerful libraries, like Pandas, NumPy, and TensorFlow, make it a popular choice for both beginners and experts.

 

Mathematics & Statistics

Mathematics and Statistics are foundational disciplines for analyzing and interpreting data, providing the tools for problem-solving and decision-making. They are essential in areas like probability theory, hypothesis testing, regression analysis, and data modeling.

 

Machine learning

Machine Learning is a subset of artificial intelligence that enables computers to learn patterns and make decisions from data without explicit programming. It involves algorithms like regression, classification, and clustering to build predictive models and automate tasks.

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