Length: 2 Days
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Data Science for Beginners: From Data to Insights Training by Tonex

Data-Science-Big-data-Analytics-Training

This comprehensive Data Science course is designed for beginners to bridge the gap between data and actionable insights. Whether you are an aspiring data scientist, analyst, or a business professional seeking to harness the power of data, this course will equip you with the foundational skills and knowledge to understand, analyze, and visualize data, leading to valuable insights.

Learning Objectives: Upon completing this course, participants will be able to:

  • Understand the fundamental concepts of data science and its applications.
  • Utilize data preprocessing techniques to clean and prepare data for analysis.
  • Apply statistical analysis to extract valuable insights from data.
  • Create visualizations that effectively communicate data-driven findings.
  • Develop a foundational understanding of machine learning and its applications.
  • Gain hands-on experience with data science tools and software for real-world data analysis.

Audience: This course is suitable for:

  • Individuals new to the field of data science seeking a strong foundation.
  • Business professionals aiming to leverage data for informed decision-making.
  • Aspiring data scientists or analysts looking to kickstart their careers.
  • Anyone interested in harnessing the power of data to gain insights and make data-driven decisions.

Course Outline:

Introduction to Data Science

  • Understanding Data Science Concepts
  • The Role of Data in Decision-Making
  • Data Science in Various Industries
  • Data Science Tools and Software
  • Ethics and Data Privacy
  • Data Science Career Paths

Data Preprocessing

  • Data Collection and Integration
  • Data Cleaning and Transformation
  • Handling Missing Data
  • Data Scaling and Normalization
  • Data Exploration and Visualization
  • Data Quality Assessment

Statistical Analysis

  • Descriptive Statistics
  • Inferential Statistics
  • Hypothesis Testing
  • Correlation and Regression
  • Probability Distributions
  • Practical Statistical Analysis

Data Visualization

  • Importance of Data Visualization
  • Types of Charts and Graphs
  • Data Visualization Tools
  • Design Principles for Effective Visualization
  • Hands-on Data Visualization Exercises
  • Storytelling with Data

Introduction to Machine Learning

  • Machine Learning Concepts
  • Supervised vs. Unsupervised Learning
  • Model Training and Evaluation
  • Classification and Regression
  • Clustering and Dimensionality Reduction
  • Real-world Machine Learning Applications

Hands-On Data Analysis

  • Practical Data Science Projects
  • Data Cleaning and Exploration
  • Statistical Analysis of Data
  • Creating Data Visualizations
  • Machine Learning Applications
  • Communicating Data Insights

This course will empower beginners with the knowledge, skills, and practical experience to confidently embark on their journey in data science and start making meaningful contributions in the data-driven world.

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