6 Best Statistical Data Science Courses & Tutorials - Learn Statistical Data Science Online
Highly curated best Statistical Data Science tutorials for beginners. Start with the best Statistical Data Science tutorials and learn Statistical Data Science as beginners.
The Best Statistical Data Science online courses and tutorials for beginner to learn Statistical Data Science in 2024.
Statistics can be a powerful tool when performing the art of Data Science (DS). From a high-level view, statistics is the use of mathematics to perform technical analysis of data. A basic visualization such as a bar chart might give you some high-level information, but with statistics we get to operate on the data in a much more information-driven and targeted way. The math involved helps us form concrete conclusions about our data rather than just guesstimating.
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Top Statistical Data Science Courses, Tutorials, Certifications list
1. Data Science Statistics for Data Scientists and Business Analysis
Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis
- Course rating: 4.5 out of 5.0 (18,858 Ratings total)
- Duration: 5 Hours
- Certificate: Certificate of completion
In this course, you will :
- Understand the fundamentals of statistics.
- Learn how to work with different types of data.
- How to plot different types of data.
- Calculate the measures of central tendency, asymmetry, and variability.
- Calculate correlation and covariance.
- Distinguish and work with different types of distributions.
- Estimate confidence intervals.
- Perform hypothesis testing.
- Make data driven decisions.
- Understand the mechanics of regression analysis.
- Carry out regression analysis.
- Use and understand dummy variables.
- Understand the concepts needed for data science even with Python and R!.
What makes this course different from the rest of the Statistics courses out there?
- High-quality production – HD video and animations (This isn’t a collection of boring lectures!)
- Knowledgeable instructor (An adept mathematician and statistician who has competed at an international level)
- Complete training – we will cover all major statistical topics and skills you need to become a marketing analyst, a business intelligence analyst, a data analyst, or a data scientist
- Extensive Case Studies that will help you reinforce everything you’ve learned
- Excellent support - if you don’t understand a concept or you simply want to drop us a line, you’ll receive an answer within 1 business day
- Dynamic - we don’t want to waste your time! The instructor sets a very good pace throughout the whole course
You can take Data Science Statistics for Data Scientists and Business Analysis Certificate Course on Udemy.
2. Data Science: Statistics and Machine Learning
Learn Data Science: Statistics and Machine Learning from Johns Hopkins University. Build models, make inferences, and deliver interactive data products. This specialization continues and develops on the material from the Data Science.
- Course rating: 4.5 out of 5.0 (13,528 Ratings total)
- Duration: 144 Hours
- Certificate: Certificate of completion
In this course, you will :
- Perform regression analysis, least squares and inference using regression models..
- Build and apply prediction functions.
- Develop public data products.
This specialization continues and develops on the material from the Data Science: Foundations using R specialization. It covers statistical inference, regression models, machine learning, and the development of data products. In the Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, learners will have a portfolio demonstrating their mastery of the material. The five courses in this specialization are the very same courses that make up the second half of the Data Science Specialization.
You can take Data Science: Statistics and Machine Learning Certificate Course on Coursera .
3. Statistics for Business Analytics and Data Science Course
Learn The Core Stats For A Data Science Career. Master Statistical Significance, Confidence Intervals And Much More!
- Course rating: 4.5 out of 5.0 (7,392 Ratings total)
- Duration: 6 Hours
- Certificate: Certificate of completion
In this course, you will :
- Understand what a Normal Distribution is.
- Understand standard deviations.
- Explain the difference between continuous and discrete variables.
- Understand what a sampling distribution is.
- Understand the Central Limit Theorem.
- Apply the Central Limit Theorem in practice.
- Apply Hypothesis Testing for Means.
- Apply Hypothesis Testing for Proportions.
- Use the Z-Score and Z-Tables.
- Use the t-Score and t-Tables.
- Understand the difference between a normal distribution and a t-distribution.
- Understand and apply statistical significance.
- Create confidence intervals and understand the potential pitfalls of overusing p-Values.
You can take Statistics for Business Analytics and Data Science Course Certificate Course on Udemy .
4. Probability and Statistics for Business and Data Science
Learn how to apply probability and statistics to real data science and business applications!
- Course rating: 4.5 out of 5.0 (3,526 Ratings total)
- Duration: 5 Hours
- Certificate: Certificate of completion
In this course, you will :
- Understand the basics of probability and be able to implement basic statistics.
- Understand how to use various statistical distributions and apply statistical methods and hypothesis testing to business problems.
- Understand how regression models work and implement one way and two way ANOVA.
- Understand Chi Squared Tests and be able to understand different types of data.
This practical course will go over theory and implementation of statistics to real world problems. Each section has example problems, in course quizzes, and assessment tests.
Including:
- Measurements of Data, Mean, Median, and Mode
- Variance and Standard Deviation and Co-variance and Correlation
- Permutations and Combinations, Unions and Intersections, Conditional Probability, Bayes Theorem, Binomial Distribution, Poisson Distribution, Normal Distribution, Sampling, Central Limit Theorem, Hypothesis Testing, T-Distribution Testing, Regression Analysis
- ANOVA, Chi Squared and much more!
You can take Probability and Statistics for Business and Data Science Certificate Course on Udemy .
5. Probability and Statistics in Data Science using Python
Using Python, learn statistical and probabilistic approaches to understand and gain insights from data.
- Course rating: 1,08,248 total enrollments
- Duration: 440 Hours
- Certificate: Certificate of completion
In this course, you will learn:
- the foundations of probability and statistics.
- concept of the mathematical theory
- get a hands-on experience of applying this theory to actual data using Jupyter notebooks.
The concepts covered during this course are random variables, dependence, correlation, regression, PCA, entropy and MDL.
The course Probability and Statistics in Data Science using Python is offered by University of San Diego on Edx.
6. Statistics & Applied Data Science - Business Data Analysis
Data Science Statistics : Data Science from Scratch for Beginners : Data Analysis Techniques, Method Course : Analytics
- Course rating: 3.6 out of 5.0 (505 Ratings total)
- Duration: 9 Hours
- Certificate: Certificate of completion
In this course, you will :
- Data analysis FAQ related to interview questions in your career.
- Practical significance versus statistical significance , and more to learn it.
- 270+ video lectures include real life practical projects and examples for people need to learn statistics for Machine learning and Data Analysis
This course material is prepared from highly experienced engineers worked in a leader companies like Microsoft , Facebook and google .
You can take Statistics & Applied Data Science - Business Data Analysis Certificate Course on Udemy .
Thank you for reading this. We hope our course curation would help you to pick the right course to learn Data Science. In case you want to explore more, you can take the free Data Science courses.
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