Mastering Statistics for Data Science

Mode: Recorded Student Live Sessions

Duration: Comprehensive 20+ Hours of In-Depth Curriculum.

Programming Language: Python

Course Language: English
Access: Lifetime

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About the course

In this course, you'll explore fundamental and advanced statistical concepts, applying them to real-world data problems and scenarios. From the basics of probability to complex statistical modeling, you'll gain the skills needed to analyze data effectively and draw meaningful conclusions. This course is ideal for data scientists, analysts, and anyone interested in mastering the statistical methods essential for data-driven decision-making.

Live Classes Lifetime Access

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Learn from Basic to Advance

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Course Content:

Basic - Intermediate Stats

Introduction to Stats

🎯 Definition and importance of statistics in data science
🎯 Types of data
🎯 Types of Stats: Descriptive vs Inferential

Descriptive Stats

🎯 Measures of central tendency (Mean, Median and Mode)

🎯 Measures of dispersion (Range, Variance, Standard Deviation, IQR)

🎯 Data visualization (Histogram, Box Plot, Bar chart, Scatter Plot)

Probability Theory

🎯 Basics of probability

🎯 Conditional probability and Bayes' theorem
🎯 Probability Distributions

Probability Distribution

🎯 Discrete Distributions (Binomial, Poisson)
🎯 Continuous Distributions (Normal, Exponential, Uniform)
🎯 Properties and applications of each distribution

Intermediate - Advanced
Linear Algebra

🎯 Vector and Vector Spaces
🎯 Matrix and Matrix Operations
🎯 Orthogonality and Projections
🎯 Eigenvalues and Eigenvectors

Sampling

🎯 Sampling Techniques (Random, Stratified, Cluster)

🎯 Central Limit Theorem

Inferential Statistics

🎯 Null and alternate hypothesis

🎯 Type | and Type || errors

🎯 P-value and significance values
🎯 t-test, chi-square test, and ANOVA

Correlation

🎯 Pearson and Spearman correlation coefficients

🎯 Interpretation of correlation coefficients

🎯 Difference between correlation and causation
🎯 t-test, chi-square test, and ANOVA

Real world applications

🎯 Case studies and examples from various domains (business, healthcare, finance)

🎯 Applying statistical methods to real datasets

Syllabus

Who can take this Course?

Tech Enthusiasts

Managers

Developers

Working Professionals

Freelancers

College Students

School Students

Interested Beings

Anyone who is looking to learn a new skill or upskill themselves can take this course

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All our programs include

Real world Projects

With real-world projects and immersive content you’ll master the tech skills companies want.

Technical Mentor Support

Our knowledgeable mentors guide your learning and are focused on answering your questions and keeping you on track.

LIVE Sessions

Get High-Quality LIVE Sessions that help you stay consistent and engaged with the course

Doubt clearing

Doubt would be discussed in the live classes

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Meet Your Mentor

Priya Bhatia, a master's graduate in AI from IIT Hyderabad, received the prestigious Reliance Foundation scholarship for her excellence in AI and computer science. She authored an IEEE-published research paper on AI in healthcare, showcasing her ability to contribute to technological advancements. With over three years of experience in Data Science with companies like Thales and iNeuron.ai, Priya has applied her academic knowledge to real-world challenges, delivering data-driven solutions. Alongside her professional achievements, she is a dedicated mentor and public speaker in Data Structures and Algorithms (DSA) and Data Science. Through her YouTube channel, "Priya Bhatia," she shares educational content, solidifying her role as a distinguished figure in the AI and Data Science field.

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Mastering Statistics for Data Science

About the course

Live Classes Lifetime Access

Watch Anywhere, Anytime

Learn from Basic to Advance

Discuss with the Educator

Course Content:

Syllabus

Who can take this Course?

All our programs include

Real world Projects

Technical Mentor Support

LIVE Sessions

Doubt clearing

Meet Your Mentor

Course Feedback