45 Courses and Certifications

Online Teaching And Academics Courses & Certifications

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Advanced Linear Models for Data Science 1 Least Squares

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Certificate

Advanced Linear Models for Data Science 1 Least Squares

The Advanced Linear Models for Data Science 1: Least Squares course helps you develop a strong foundation of linear and regression modelling. Johns Hopkins University offers the programme, and your instructors will be subject-matter experts. It is the third part of the Advanced Statistics Specialisation by Coursera.  

Moreover, the course completion certificate that you will receive is shareable, after finishing the Advanced Linear Models for Data Science 1: Least Squares programme by Coursera. It will allow you to establish your relevant expertise in the field. Learn and develop fluency in the basics related to least squares and regression modelling, at your own pace.

In addition, the Advanced Linear Models for Data Science 1: Least Squares course features immersive content, developed around a self-paced model to align perfectly with your schedule. The training also provides adjustable deadlines. Furthermore, the online course allows you to quickly and efficiently start studying. You have to devote nearly 8 hours of learning time to the programme.

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3 Weeks
Expert
3,369
Skills Covered:
R Programming Knowledge of Applied statistics
Probabilistic Graphical Models 2 Inference

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Certificate

Probabilistic Graphical Models 2: Inference

Probabilistic Graphical Models (PGMs) is considered to be a strong foundation for encrypting probability arrangement over composite domains. Hence, Probabilistic Graphical Models 2: Inference is drafted to address the questions related to probabilistic inference. This course depends upon the concepts from graph algorithms, probability theory, and machine learning. These concepts are the base for the advanced methods used in various applications like speech recognition, medical diagnosis, natural language processing, etc. These advanced methods are also essential tools in composing various machine learning problems.

In an order of three, Probabilistic Graphical Models 2: Inference is the second one. While the first course, focused on description, this course would address the question occurs in probabilistic inference or in other words use of PGM in answering the questions. PGM is described as a very high dimensional diffusion but its framework is drafted in such a way that it can answer the questions efficiently. The course introduces both approximate and accurate algorithms for the variety of inference tasks, and also talks over the application of each algorithm.

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3 Weeks
Expert
5,029
Skills Covered:
Knowledge of Algorithms Knowledge of Monte Carlo Method
Bayesian Statistics Mixture Models

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Certificate

Certification Course on Bayesian Statistics: Mixture Models

This certification course in Bayesian Statistics: Mixture Models by Coursera is a one stop place to learn the Bayesian Statistics and its Mixture Models along with its applications in the practical world. The course introduces one of the useful classes of statistics. This course is structured in a way to teach the most practical uses of Bayesian Statistics and its tools. It encourages candidates taking this course to practice and learn as the course progresses by not simply watching the videos but also constantly solving the Bayesian Statistics problems.

The course also utilises the industry software R in some places for solving the course problems. R is an easily available free statistical software that is used in m multiple industries of development, design and manufacturing, etc. The course lays out a basic tutorial to learn the software and teach the uses of it in Bayesian Statistics. Candidates are also encouraged to learn further about R for better advantages in their career.

The course is an intermediate level certificate course in Bayesian Statistics: Mixture Models taught by some of the expert faculty of the University of California Santa Cruz. For candidates who wish to take this course, it should be noted that prior knowledge of principles of estimation in maximum likelihood, Calculus based probability, and the Bayesian estimation is required. The course is a great way to take a step further in the statistics learning field and can provide you with the required edge in your career and the industry.

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3 Weeks
Intermediate
13,514
Skills Covered:
Statistical skills
Statistical Inference

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Certificate

Statistical Inference

3 Weeks
4,117
Statistics with SAS

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Certificate

Statistics with SAS

3 Weeks
Intermediate
Free
Certificate

Causal Inference 2

3 Weeks
Expert
Free

Offered by

Certificate

Introduction to Statistics

32 Hours
Free
Probabilistic Graphical Models 1 Representation

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Certificate

Probabilistic Graphical Models 1: Representation

The Probabilistic Graphical Models 1: Representation course by Coursera is a part of the Probabilistic Graphical Models Specialization on the Coursera platform. Stanford University offers a certification course in association with Coursera.

The Probabilistic Graphical Models 1: Representation online course has a curriculum spread out over five weeks. The certification course will help you develop a deep understanding of the PGM framework by communicating perplex material with skill. Moreover, the online course primarily covers the fundamentals of Bayesian networks and Markov networks. 

Furthermore, the Probabilistic Graphical Models 1: Representation certification course promotes interaction and improvement with a comprehensive curriculum, intermittent assignments, and discussion boards. Candidates can self-assess using these mediums and grasp the course contents at their own pace. 

Finally, Coursera provides a certificate upon successful completion of the  Probabilistic Graphical Models 1: Representation course. The certificate can be added to the resume or shared on LinkedIn and other professional websites. Learners can also take a print out of the certificate.

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Expert
5,029
Skills Covered:
Machine learning
Fundamentals of Data Science and Statistics

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Certificate

Fundamentals of Data Science and Statistics

The Fundamentals of Data Science and Statistics course will help you develop a foundation in the fundamentals of data science and statistics. The program will take you through multiple core concepts through a hands-on approach. The faculty for this training boasts over 20 years of teaching experience and has ample skills in the relevant field. 

Furthermore, the Fundamentals of Data Science and Statistics program takes you through probability concepts, hypothesis testing, and linear regression essentials. Additionally, the curriculum of the training emphasizes advanced linear regression. You will get to know about multiple regression, ANOVA table, serial correlation, and other related concepts.

This Fundamentals of Data Science and Statistics online course by E & ICT Academy (IIT Kanpur) houses assignments and a course-end assessment to help you acquire a course certificate. You will have the opportunity of attending live sessions with the course instructor. Moreover, there will be a total of five lectures only.

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5,000
Skills Covered:
Statistical skills Data science knowledge

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Certificate

Master Statistics with Python

The Master Statistics with Python programme on Codecademy is a skill path curriculum. The course covers vital concepts about one of the most in-demand programming languages, Python. As such, you’ll develop a specialised skill in using Python for running hypothesis tests and summarising data. 

Besides, hand-picked content is provided in this training to help you fast-track your learning and complete the course in a few months. Codecademy offers a vast Master Statistics with Python certification syllabus. 

You will gain comprehensive knowledge on quantitative data stats, probability, visualising categorical data, and other related topics. Moreover, these skills will make you fluent in communicating data, testing your theories, and establishing a firm Python expertise. 

With Codecademy’s Pro plan, you can get extra benefits for the Master Statistics with Python course. You’ll become a part of the Pro members’ community, get unlimited programme access, work on real-world projects, and receive a step-by-step training roadmap. The Pro subscription also includes additional lessons on experimental design, SciPy, matplotlib, NumPy, and more.

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Intermediate
Skills Covered:
Knowledge of Python Knowledge of Numpy

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Certificate

Intro to Inferential Statistics

The Intro to Inferential Statistics online course is free of cost programme which is brought to the students by Udacity. Candidates who enrol on the course will be able to pursue this programme in online mode. 

The Intro to Inferential Statistics syllabus includes seven chapters along with various exercises and interactive quizzes and students will be able to complete the entire curriculum in the time period of two months. The course is a self-paced programme and can be pursued without any time limitations according to the schedule of the participants. Students can access the Intro to Inferential Statistics Course at any time depending upon their requirements.

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Skills Covered:
Statistical skills
Statistics

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Certificate

Statistics

Candidates who join the programme will be gaining plenty of information regarding data, variables, research methods, distribution analysis, and other related aspects. The course is available for all the interested students at absolutely zero cost. Candidates can complete the curriculum in online mode through the website named Udacity. 

Students who take up the course can access the course 24x7 without any limitations as the course is a self-paced programme. The course comprises a total of six lessons that can be completed in the time span of four months. Students get to learn from the Statistics syllabus through interactive video sessions and quizzes throughout the programme.

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Skills Covered:
Statistical skills

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Certificate

Probability and Statistics for Business and Data Science

The Probability and Statistics for Business and Data Science online course is a 5 hours on-demand program offered by Udemy which consists of 10 articles and 35 downloadable resources. The course teaches about the basics of probability. This hands-on course will cover statistics theory as well as how to apply statistics to real-world issues. Each module includes sample problems, in-class quizzes, and assessment exams. 

The Probability and Statistics for Business and Data Science training begin by discussing the fundamentals of data, including how to evaluate it using measures of dispersion and central tendency, as well as how bivariate data sources may be related to one another. Following that, the course will delve into learning about combinations, probability, and conditional distribution and well as permutations and how to use the Bayes theorem.

The Probability and Statistics for Business and Data Science syllabus cover the most common distributions encountered in statistics, laying the groundwork for knowing how to work with binomial, uniform, normal, and Poisson distributions.

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3,499
Skills Covered:
Statistical skills Data science knowledge

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Certificate

Central Limit Theorem

Beginner
Free

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