Accenture Offering Free Probability & Statistics Course – Apply Now 2024

Are you looking to enhance your skills in probability & statistics? Accenture is offering a free probability & statistics course, which is open to anyone interested in learning. This course is designed for those with no prior knowledge of statistics, and its only prerequisite is basic algebra.

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About the Accenture

Accenture plc is an Irish-American professional services company based in Dublin, specializing in information technology (IT) services and consulting. A Fortune Global 500 company, it reported revenues of $64.1 billion in 2023. Accenture’s current clients include 91 of the Fortune Global 100 and more than three-quarters of the Fortune Global 500. As of 2022, Accenture is considered the largest consulting firm in the world by number of employees

Accenture began as the business and technology consulting division of accounting firm Arthur Andersen in the early 1950s when it conducted a feasibility study for General Electric to install a computer at Appliance Park in Louisville, Kentucky, which led to GE’s installation of a UNIVAC I computer and printer believed to be the first commercial use of a computer in the U.S. Joseph Glickauf, an early pioneer of computer consulting, held a position as head of Arthur Andersen’s administrative services division

Highlights of the course

This course is a part of the AI Ascend program.

Probability and statistics form the foundation of data science.

This course will give the students a thorough understanding of probability theory, different kinds of probability distributions, testing hypotheses for mean and proportion, as well as dimensionality reduction.

A thorough experience with NumPy, SciPy, and sci-kit-learn packages is an additional strength of this course.

Job Roles-

Data Scientist

What is the Probability & Statistics course?

A Probability & Statistics course is an introduction to the world of data analysis. It equips you with the tools to understand, analyze, and interpret data. Here’s a breakdown of what you’ll typically learn:

Probability:

This branch of mathematics deals with chance and uncertainty. You’ll learn concepts like:

Probability of events happening

Different ways to calculate probabilities (e.g., counting methods)

Conditional probability (how the likelihood of one event affects another)

Common probability distributions (e.g., normal distribution, binomial distribution)

Statistics:

This field focuses on collecting, summarizing, analyzing, and drawing conclusions from data. You’ll cover topics like:

Descriptive statistics: summarizing data with measures like mean, median, and standard deviation

Data visualization: creating charts and graphs to understand data patterns

Inferential statistics: using samples to make inferences about larger populations (e.g., hypothesis testing)

Statistical modelling: building models to identify relationships between variables

Eligibility Criteria

BE/ BTech students-any stream

Non-engineering students-STEM background

Working Professionals

What will You Learn Free Probability & Statistics course?

At the end of this course, you should be able to:

Understand the concept of probability and its relation with mathematical sets

Be able to perform basic operations with sets and probabilities and use them to answer interesting questions

Contrast population and sample, parameter and its estimate

Understand and contrast the concepts of basic summary statistics, e.g., mean, variance, standard deviation, etc. for population versus samples and learn to estimate them from data

Understand the concept of effect size and uncertainty

Have a comprehensive idea about different kinds of probability distributions both discrete and continuous

Understand the concept of hypothesis, type I and II errors, level of significance, and power

Understand and be able to test hypotheses for mean and proportion and draw useful inferences from the process

Define and recognize the relation between covariance and Pearson’s correlation coefficient

Recognize the importance of dimensionality reduction, and comprehend principal component analysis. Along the way, you will learn about different matrix factorization techniques, eigenvalues, eigenvectors, their properties and interpretation

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Why should you enroll in Free Probability & Statistics course?

At the end of this course, you should be able to:

Understand the concept of probability and its relation with mathematical sets

Be able to perform basic operations with sets and probabilities and use them to answer interesting questions

Contrast population and sample, parameter and its estimate

Understand and contrast the concepts of basic summary statistics, e.g., mean, variance, standard deviation, etc. for population versus samples and learn to estimate them from data

Understand the concept of effect size and uncertainty

Have a comprehensive idea about different kinds of probability distributions both discrete and continuous

Understand the concept of hypothesis, type I and II errors, level of significance, and power

Understand and be able to test hypotheses for mean and proportion and draw useful inferences from the process

Define and recognize the relation between covariance and Pearson’s correlation coefficient

Recognize the importance of dimensionality reduction, and comprehend principal component analysis. Along the way, you will learn about different matrix factorization techniques, eigenvalues, eigenvectors, their properties and interpretation

Curriculum

We will begin by introducing the notion of mathematical sets before moving on to the idea of probability.

In addition to learning the fundamentals of probability, students will gain an understanding of conditional probability and the Bayes theorem.

The concept of the various probability distributions—both discrete and continuous—will next be developed using pertinent examples.

The ideas of various summary statistics, such as mean and variance, will be covered in between.

Additionally, students will learn how to use principal component analysis, correlation, and covariance to examine patterns among many variables.

The instruments covered in the Free Probability and Statistics course

Overview of sets

probability and fundamental set operations

Multiplex and sum ‘rules’ of probability

Distributions of probabilities

Both continuous and discrete probability distributions

Testing of hypotheses

Chi-squared and T-tests

Covariance

Relationships

Analysing the principal components

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How To Apply?

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