EDA and Data Visualization Course in Data Science
Free EDA and Data Visualization Course in Data Science Online with Certificate
Srikanth Varma,
Lead DSML Instructor at Scaler
About this Free EDA and Data Visualization Course in Data Science
This free EDA (Exploratory Data Analysis) and Data Visualization course offers learners a comprehensive understanding of data analysis techniques and visualization tools. Designed for beginners and professionals, the course focuses on practical applications, using open-source tools like Python, Pandas, and Matplotlib for hands-on learning and real-world problem-solving.
5
Audio: English
Subtitles: English
Duration
17h 28m (7 Modules)Challenges
6 ChallengesCourse Level
BeginnerCertificate
IncludedWhat you’ll learn
The skills that you would learn after taking up this EDA and Data Visualization Course in Data Science online course are:
- EDA or Exploratory Data Analysis is an approach to deal with and analyze large sets of data using various visualizing techniques.
- After completing our free course, the learner will have an understanding of various topics related to EDA such as Plotting for Exploratory Data Analysis (EDA), Linear Algebra, Probability and Statistics, Dimensionality Reduction and Visualization, etc.
- The learner can advance and search for job roles in the field of EDA and data science in particular.
Course Content
7 Modules | 94 Lessons | 17h 28m
Certificate for Free EDA and Data Visualization Course in Data Science
After successfully completing the course, you’ll be awarded with Certificate Of Excellence from Scaler
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Instructor of this course
Lead DSML Instructor at Scaler
2000+ Students on Scaler Platform
600+ Hours of Lectures Delivered
5 Star Instructor on Scaler
9 Courses
- Co-Founder & Principal Instructor, Applied AI & AppliedRoots
- Senior ML Scientist @ Amazon, Palo Alto and Bangalore
- Co-Founder, Matherix Labs
- Research Engineer, Yahoo! Labs
- Masters from IISc Bangalore, Gate 2007(AIR 2)
- 13 years of experience in AI and Machine Learning
Pre-requisites for free Data Visualization certification course
- EDA and Data Visualization in Data Science free course
- Perfect for beginners: No prerequisites required
- Beneficial for those with Python, EDA, and data Visualization knowledge
- Ideal for advancing in Data Science
- Provides a revision of basic understanding and introduces Data Science-specific modules, tools, and use cases
- Includes numerous questions for each topic to strengthen concepts
- Comprehensive course coverage
- Not just focused on Data Science Visualization
- Get ready for both EDA and Data Visualization in Data Science with this single course
Who should learn this Data Visualization course for Beginners?
- Ideal for beginners in IT: This course is designed to help you elevate your programming journey and advance into Data Science by learning data Visualization and EDA.
- Self-determination and basic programming knowledge required: You can go from zero to hero with determination and a basic understanding of programming.
- Comprehensive course design: The course is structured to ensure users understand all concepts thoroughly.
- Suitable for non-beginners too: If you already have experience with Python programming and Data Science concepts, this course can serve as a revision tool.
- Covers basic to intermediate-level concepts: Learn EDA and data Visualization from the ground up.
- Practice through questions: Each concept is reinforced with questions to help you brush up on your understanding.
FAQ related to this course
What is EDA and Data Visualization in Data Science?
Exploratory Data Analysis (EDA) is a crucial step in data science that involves analyzing and summarizing datasets to uncover patterns, trends, and insights. Data visualization, a key component of EDA, is the graphical representation of data using plots, charts, and graphs. These visualizations help data scientists to better understand the underlying data structure, identify outliers, and detect relationships among variables, thereby enabling more effective decision-making and communication of insights to stakeholders.