bestcourses is supported by learners. When you buy through links on our website, we may earn an affiliate commission. Learn more
Data Analysis for Business and Finance
Learn Data Analysis: Descriptive & Inferential Statistics, Regression Analysis, Time Series and much more!
Created by Saurav Singla, offered on Udemy
To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 21628 students which left 123 reviews at an average rating of 3.3, which is average.
We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 4 hours 34 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 5 hours 20 minutes.
This course currently has a bestcourses score of 6.2/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.
In these volatile and continuously evolving times, there’s no dearth of data available from multiple sources. Therefore, it becomes imperative that such data is validated and converted into meaningful information that can be used to make optimal decisions.
This course exactly focuses on this and exposes you to various tools and methods that can be used to interpret data and derive information. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization.
If you are aiming for a career as a Data Scientist or Data Analyst then lay foundation on your Statistics, Regression, Time Series skills are a few things you wish to try and do. It covers the essentials of descriptive, predictive, and prescriptive analytics. It focuses on problem-solving by model development and solution interpretation. Use appropriate Data Analysis techniques for real-world problems and data. Write comprehensive and critical reports evaluating and interpreting obtained results.
So many courses and books just bombard you with the theory, and math, and coding... But they forget to explain, perhaps, the most important part: why you are doing, what you are doing. And that is how this course is so different. We focus on developing an intuitive feel for the concepts behind Data Analysis.
With our intuition tutorials, you will be confident that you understand all the techniques on an instinctive level. This is a game-changer for both business managers and finance professionals who can now learn techniques to maximize their knowledge and skills.
In conclusion, this is an exciting training program filled with intuition tutorials and techniques that can be applied to all sets of data to make decisions that can benefit you in both personal and professional life.
We are super enthusiastic about Data Analysis and hope to see you inside the class!
What you will learn
- Understand Statistics from basic to advance level
- Learn Descriptive and Inferential Statistics
- How to plot different types of data
- Exploratory data analysis: graphical and numerical approaches (Mean, Mode, Standard Deviation etc)
- Exploring data analysis: Univariate and Bivariate Analysis
- Calculate Covariance and Correlation
- Understand the Central Limit Theorem
- Understand standard deviations
- Probability: Essentials and Conditional Probability
- Distinguish and work with different types of Probability Distributions (advance level distributions covered extensively)
- Calculate the measures of Central Tendency, Asymmetry, and Variability
- Understand what a Sampling and Estimation is
- Statistical Inference: Perform Hypothesis testing and Estimate Confidence Interval (from basics to deep dive)
- Regression Analysis and estimating relationships among variables (including complex level of testing with F-statistics and T-tests)
- Time-Series: Simple/Linear/Moving Average/Exponential, Smoothing techniques, Seasonality, Decomposition methods
- Make data driven decisions using the above (covering examples)
- No prior knowledge or experience is required. We start from the basics and gradually build up your knowledge and skills.