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Statistics and Probability for Data Sciences

A comprehensive course on Statistics and Probability for Data Sciences.

12 weeks long course | 100% Online

Learn from leading experts in the industry

Project based learning with 2 industry level projects that learners can showcase on LinkedIn.

Learn Key Tools & Technologies Jupyter Notebook

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Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

  • The students will gain a thorough knowledge of statistics and probability and their use in various machine learning algorithms.
  • During the course work, the students will learn about,
    • Probability and statistics 
    • An introduction to,
      • Machine learning
      • Artificial intelligence
      • Deep learning
    • Set theory
    • Descriptive statistics
    • Discrete and continuous probability distribution
  • Students are exposed to the modern trends and standard practices followed in the industry right now.

Course Syllabus

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week 01 - Introduction to Machine Learning

  • This week we will learn about 
    • Introduction to Artificial Intelligence 
    • Introduction to Machine Learning
    • Supervised, Unsupervised, and Reinforced Learning
    • Introduction to Deep Learning
    • Modules needed to implement a Machine Learning model

Week 02 - Set Theory

  • This week we will learn about 
    • Set Theory
    • Algebra of Sets
    • Venn Diagrams

Week 03 - Probability

  • This week we will learn about 
    • Introduction to Probability
    • Axioms of Probability
    • Independent events
    • Mutually exclusive events
    • Conditional Probability
    • Bayes Theorem

Week 04 - Statistics

  • This week we will learn about 
    • Measures of Central Tendence
    • Measures of Dispersion
    • Measures of Symmetry

Week 05 - Probability Distribution

  • This week we will learn about
    • Concept of Random variable
    • Bernoulli distribution
    • Binomial distribution
    • Negative Binomial distribution
    • Geometric distribution
    • Hypergeometric distribution
    • Poisson distribution
    • Uniform distribution
    • Probability mass function and cumulative distribution function
    • Brief intro to Gamma exponential and normal distribution

Week 06 - Continuous Probability Distribution

  • In this week, we will learn 
    • Continuous distributions
    • Normal Distribution
    • Gamma Distribution
    • Exponential Distribution
    • Lognormal Distribution
    • Weibull Distribution
    • F Distribution
    • T Distribution
    • chi square Distribution
    • Probabiltiy Density Function 
    • Cumulative Distribution Function 

Week 07 - Inferential Statistics

  • This week we will learn about 
    • Sampling
    • Probabilistic and Nonprobabilistic methods of Sampling Estimation
    • Estimation
    • Sample size estimation

Week 08 - Hypothesis Testing

  • This week we will learn about 
    • Introduction to hypothesis testing
    • Rejection region
    • Critical value
    • p-value

       

Week 09 - Hypothesis Testing

  • This week we will learn about,
    • z - test
    • f - test
    • t - test
    • Anova - test 

Week 10 - Non-Parametric Tests

  • This week we will learn about
    • Chi square test
    • Mann Whitney U test
    • Kruskal Wallis test
    • Sign test
    • Correlation
    • Chi square
    • Karl Pearson
    • Spearman Coefficient
    • Regression between variables
    • Implementation of statistical functions in Jupyter notebook

Our courses have been designed by industry experts to help students achieve their dream careers

Industry Projects

Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 2 Projects that are available in this program.

Analysis of Medical Insurance Data

For this project, learners are to do the following:

  • The objective is to find the insurance premium and give the patients' details.
  • The data, which contains various parameters such as age, gender, etc., is given to the students.
  • The student is expected to perform descriptive statistics and outline the various parameters of the data.
  • The student should perform some exploratory data analysis to understand the dataset much better.
  • Given the client parameter, the student is expected to find the insurance premium.

Analysis of Fermented Drink Data

For this project, learners are to do the following:

  • Analyze the quality of two types of fermented drinks.
  • The student will perform descriptive and inferential statistics on the data set.
  • The dataset contains the chemical composition of various types of fermented drinks and the ratings they got.

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.6

Become an Ace Data Scientist with the Statistics and Probability for Data Sciences Course

According to the US Bureau of Labour Statistics, job opportunities for data scientists are expected to increase up to 36% by 2030. It translates to 113,300 new jobs in the current decade.

Skill-Lync’s Statistics and Probability for Data Sciences is a 12-week online course. It will teach you how to use statistical skills for developing ML and AI algorithms. An industry expert with nine years of experience has carefully curated the course. As the Statistics for data science course curriculum strictly adheres to industry standards, it will help you become job-ready. Two industry-level projects are included in the curriculum to provide you with hands-on practice.

The advanced topics in statistics for data science will help you build the skills necessary to kickstart a career in the construction industry. The fee for learning the Statistics and Probability for Data Sciences ranges from INR 6,000 to INR 12,500 monthly for three months.

Who Should Take This Course?

The industry-oriented Statistics and Probability for Data Sciences course is for students and graduates of computer science and related streams of engineering. If you are interested in topics related to maths, statistics and probability, this course is for you. Experienced professionals looking for a career transition to this domain can opt for this course.

What will you learn?

The course will take you through basic statistics for data science and machine learning concepts. The following topic will be dealt with in this course:

  • Supervised, Unsupervised, and Reinforced Learning of ML
  • Set Theory
  • Probability Distribution
  • Non-Parametric Tests

Skills You Will Gain

  • Ability to develop efficient machine learning algorithms with insights from statistical analysis.
  • Complete knowledge of standard industry practices and modern trends.
  • Proficiency in using the tools like Jupyter Notebook.

Key Highlights of The Program

  • Statistics and Probability for Data Sciences is a 12-week course.
  • Besides the course completion certificate for all participants, the top 5% of learners get a merit certificate.
  • You will get email and forum support to clear your doubts during the course.
  • Real-time industry-relevant projects will make your learning purposeful and practice-oriented.

Career Opportunities after taking the course

Upon completing the Statistics and Probability for Data Sciences course, numerous job opportunities will open up for you. Some exciting positions that you can work for include:

 

  • Business Analyst
  • Data Analyst
  • Data Scientist

 

FAQs on Statistics and Probability for Data Sciences Course

  1. Who can take the Statistics and Probability for Data Sciences course?

Students and graduates of computer science and related engineering streams can take up the Statistics and Probability for Data Sciences course.

  1. Is Statistics and Probability for Data Sciences an online program?

Yes, the statistics for the data science course are 100% online.

  1. What is the duration of the Statistics and Probability for Data Sciences course?

The advanced topics in statistics for data science can be covered in a duration of 12 weeks.

  1. What is the fee for pursuing the Statistics and Probability for Data Sciences course?

The fee for learning the basic statistics for data science at Skill-Lync is flexible and is available in three plans. The basic plan provides you with two months of access at INR 6,000 per month, the Pro plan provides four months of access at INR 8,500 per month, and the Premium plan provides you lifetime access at INR 12,500 per month.

  1. How are statistics used in data science?

Statistics is the core knowledge essential for any data scientist. Statistics methods are deployed in data science to determine the patterns or behaviour of users. 

  1. How much can a data scientist earn?

According to Glassdoor, the average annual salary of a data scientist ranges from INR 4 LPA to 11 LPA. However, your pay package may vary with your experience and expertise.

  1. Is there any certificate for completing the Statistics and Probability for Data Sciences course?

Yes, you shall be given a course completion certificate after completing the Statistics and Probability for Data Sciences course. The top 5% of the scorers will receive a merit certificate alongside the course completion certificate.

  1. Is any technical support available for these statistics for the data science course?

Yes, you can clear your doubts during coursework from our technical support team through email and forum support.

  1. Can you tell me more about Skill-Lync?

Skill-Lync is among India’s leading EdTech platforms dedicated to transforming engineering education. We equip young engineers with the latest skill sets and cutting-edge tools in new-age technologies.

The brainchild of two engineers from Chennai, Skill-Lync, is on a mission to bridge the skill gap between aspiring professionals and the industry’s demands through job-oriented courses.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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9 years in the experience range

Instructors with 9 years extensive industry experience.

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Areas of expertise

  • Physics

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