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Mastering Probability and Combinatorics

person icon AKHIL VYDYULA

4.6

Mastering Probability and Combinatorics

Mastering the Essentials: Probability and Combinatorics Explained

updated on icon Updated on Jun, 2025

language icon Language - English

person icon AKHIL VYDYULA

category icon Teaching and Academics ,Math,Probability

Lectures -7

Duration -2 hours

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4.6

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Course Description

Dive deep into the fascinating world of probability and combinatorics with this comprehensive course designed for aspiring statisticians and data analysts. Over 1 hour and 24 minutes, you will explore fundamental concepts such as random experiments, sample spaces, and the intricate relationships between events. Gain a solid understanding of combinations and permutations, and learn to distinguish between vectors and scalars. This course also includes hands-on activities using Google Colab to analyze central tendency, dispersion, and hypothesis testing with P-values. By the end, you’ll be equipped with the skills needed for statistical analysis, forecasting trends, and making informed decisions.

Goals

  • Understand the basic concepts of probability, including events, sample spaces, and outcomes.
  • Explore the principles of probability, including the addition and multiplication rules.
  • Dive into different probability distributions, such as the binomial, Poisson, and normal distributions.
  • Discover real-world applications of probability in various fields, such as statistics, finance, and science. 

Prerequisites

  • Mathematical Background: Typically, students are expected to have a strong foundation in basic mathematics, including algebra and calculus. Understanding concepts like mathematical notation, functions, and equations is crucial.

  • Combinatorics Fundamentals: Some familiarity with basic combinatorial concepts, such as permutations, combinations, and the counting principles, can be useful.

  • Probability Basics: A basic understanding of probability theory can be helpful, but it's not always a strict prerequisite. The course may start with the fundamentals.

  • Course-Specific Prerequisites: Check the course description or contact the instructor or institution to see if there are any specific prerequisites for that particular course. Some courses might have additional requirements.

Mastering Probability and Combinatorics

Curriculum

Check out the detailed breakdown of what’s inside the course

Unveiling Uncertainty: Exploring Probability Basics and Random Experiments

1 Lectures
  • play icon Mastering Probability and Combinatorics 02:54 02:54

Laying the Foundation: Understanding Sample Spaces and Events in Probability

1 Lectures
Tutorialspoint

Unlocking the World of Combinations and Permutations in Combinatorics

1 Lectures
Tutorialspoint

Distinguishing Vectors from Scalars: Understanding the Fundamental Differences

1 Lectures
Tutorialspoint

Unlocking the Mysteries of Probability and Combinatorics: A Hands-On Approach

1 Lectures
Tutorialspoint

Data Analysis with Google Colab: Exploring Central Tendency, Probability

2 Lectures
Tutorialspoint

Instructor Details

AKHIL VYDYULA

AKHIL VYDYULA

Data Scientist | Data & Analytics Specialist | Entrepreneur

Hello, I'm Akhil, a Senior Data Scientist at PwC specializing in the Advisory Consulting practice with a focus on Data and Analytics.

My career journey has provided me with the opportunity to delve into various aspects of data analysis and modelling, particularly within the BFSI sector, where I've managed the full lifecycle of development and execution.


I possess a diverse skill set that includes data wrangling, feature engineering, algorithm development, and model implementation. My expertise lies in leveraging advanced data mining techniques, such as statistical analysis, hypothesis testing, regression analysis, and both unsupervised and supervised machine learning, to uncover valuable insights and drive data-informed decisions. I'm especially passionate about risk identification through decision models, and I've honed my skills in machine learning algorithms, data/text mining, and data visualization to tackle these challenges effectively.


Currently, I am deeply involved in an exciting Amazon cloud project, focusing on the end-to-end development of ETL processes. I write ETL code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, and execute scripts via EMR services. The processed data is then loaded into Postgres SQL (RDS/Redshift) in full, incremental, and live modes. To streamline operations, I’ve automated this process by setting up jobs in Step Functions, which trigger EMR instances in a specified sequence and provide execution status notifications. These Step Functions are scheduled through EventBridge rules.


Moreover, I've extensively utilized AWS Glue to replicate source data from on-premises systems to raw-layer S3 buckets using AWS DMS services. One of my key strengths is understanding the intricacies of data and applying precise transformations to convert data from multiple tables into key-value pairs. I’ve also optimized stored procedures in Postgres SQL to efficiently perform second-level transformations, joining multiple tables and loading the data into final tables.


I am passionate about harnessing the power of data to generate actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, I would love to connect. Let’s explore the endless possibilities that data analytics can offer!

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