Business Analytics

Introduction to Linear Algebra for Data Science The importance of Linear Algebra in Data Science:  Linear Algebra is a part of mathematics that handles solving systems of linear equations. It deals with crucial concepts of Data Science such as vectors, matrices, and linear transformations. It is pretty important to acquire an understanding of Linear Algebra if you are working with data so that you are able to perform the data transformations. Assuming that the data/math you are inputting and working with is correct, you will manipulate the data in an efficient manner. The more advanced you get with your math skills the more you can dive into deeper learning models.  The basic building blocks of Linear Algebra:  The basic building blocks of Linear Algebra include the vectors, matrices, and the linear transformations. These building blocks allows for us to manipulate data in an organized approach. What is the function of each one of these concepts? Let's look at Vectors. Ve...

Differences between Generative and Conventional AI  Generative AI: As technology develops our jobs begin to change as well. In the workforce AI skills will at some point be expected from a greater number of employees. Generative AI is focused more on the basic fundamentals of AI. It includes software's that generate text, images/graphics, video, etc. The goal of this type is just that, to create and duplicate real human projects/ideas. For anyone that's curious or wants to get a feel for AI, there are software's that have a free version such as ChatGPT. For work/career, generating is the tool people should learn. This can be seen as more of an introduction. Conventional AI (Traditional): Conventional AI is also known as Traditional AI. This form of AI requires some more advanced background with math/coding. That is because Conventional AI is more than just generating and producing human like work. This focuses on making decisions/coming up with answers that backs up a set o...

  Handling and Cleaning Data with Python Libraries Introduction to Pandas/How to Import Data What is pandas? Pandas is a library within the Python software that is open to creators worldwide. This library holds prewritten codes and data structures that can be modified and used on any set of data. It's very time efficient and flexible as it easily allows users to implement these functions/features onto their own projects/collaborations.  1. How do you use Pandas in Python? To use Pandas you import the library: "import pandas as pd" There are two primary data structures.  Series: A series holds any data type. It is a one-dimensional array.  DataFrame: A dataframe is a two-dimensional array that holds different types of data.  2. How do you import data with pandas? Pandas allows users to import data from softwares like Excel, JSON, CVC, SQL. Steps on importing data to pandas.  - import pandas as pd - # Reading data from a CSV file data = pd.read_csv ('data....

Work Simplified? The way we problem solve and do math today may be simplified as technology keeps on evolving. This may be beneficial for those who are in fields that are math and problem solving heavy.  When I first started college back in 2019, the talk of coding or even AI wasn't really a thing unless you were in a field yourself that dealt with coding or advanced math. AI was a word I had not heard of much in those years. Especially in accounting it wasn't really brought up. I'm sure it was a talk; it just wasn't as concerning in my studies. With careers such as computer science, engineering, mathematics; I can really see how they are affected by the ongoing development of AI.  After having some hands-on experience with these software's myself, I do agree with Professor Kelsey that these AI tools are beneficial to learn. There's no doubt AI will make the job easier with coding/math. It can be as simple as giving ChatGPT a prompt and having it type out a scri...

  Thoughts on Accounting and AI  As an accounting major, I've already been hearing about AI being implemented into the industry. Some concerns may pop into mind right away, but there may be some benefits to it as well. I know the more popular concern is whether AI will take over our jobs. Will we be competing with technology for a chance to work? How could we ever compete with technology that may be faster or smarter than us? These are some questions that in my previous classes have been brough up and discussed. What we have gone over in my accounting courses and even previous BALT courses like Mgr Decision Making Under Uncertainty (we went over AI and ChatGPT) is that yes, AI is already makings its way into our daily lives, and we will find technological changes somewhere down the line.  In the accounting field, AI might change the procedures that accountants are used to. Such as the way they create financial statements and put data into the system. Software is definitel...