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Financial modeling is really as much an art as it is a science, but there are some basic tips that you should adhere to when you're building financial models.  First of all, you need to understand that Excel is the main tool used by a variety of institutions,...

The art of financial modeling, mostly relates to making assumptions about the future performance of the business being modeled. This is the most subjective, but also the most important part in valuation of a firm. In particular, there's four different types of...

The first step in many financial models is linking the different financial statements together. In point of fact, this actually seems trivial. It doesn't seem too hard to put together the income statement with the balance sheet, right. But in reality it can be...

One of our first tasks in building out a financial model, especially a three-statement financial model is to go through and evaluate the financial statements and make sure they're complete. Now what we have here are three different financial statements for a b...

While building out the income statement and the balance sheet portion of the three-statement financial model is usually fairly straightforward, building out the statement of cash flows can be a little bit trickier because it often draws from the income stateme...

Building financial models really starts when we begin making assumptions about what's going to happen to the business over time. In particular, in order to get to future assumptions, we're going to have to start by examining what's happened historically. I'm i...

Once we've gone through and built out our financial assumptions based on the historical figures, it's time to move on to the forward-looking portion of those assumptions. I'm in the 02_06_Begin excel file. Now, we've gone through and computed various historica...

Once we've made a set of forward-looking assumptions about how we think the firm's revenue, cost and assets and liabilities will change over time, we're prepared to then begin making projections about the firm's financial condition on a forward-looking basis. ...

Once you've finished building your three-statement financial model, there are a few things you can check to make sure you have all the right parts and pieces in place. To begin with, you want to make sure that you've translated all of your value drivers: price...

Building out a financial model is not as hard as it seems. Let's take a step back and look at the overall process. There are six steps in building a financial model.  Step one involves going through and gathering the data that we need to build that model. Typ...

If we've built our financial model correctly, when we get done, the whole model should be tied together so that any change to the model dynamically updates across the entire spreadsheet. This is very useful when dealing with practical problems like the need to...

While there a lot of different ways to build financial models, one of the great features that's unique to Excel is the ease of adding graphics, right? We all know that while numbers are interesting, there's an awful lot of business people out there that really...

Business valuation is a common task in the investments world, and a financial model is the typical approach to handling issue. In this video, we'll talk about an overview of how valuation models work. Now a valuation model uses expected cash flows, along with ...

One of the tasks that you'll probably run into if you're trying to build a financial model is the need to value the firm. This is going to start with determining what the cash flows for that firm are going to be. Now, that sounds simple enough, right? We could...

You are building an ML model to detect anomalies in real-time sensor data. You will use Pub/Sub to handle incoming requests. You want to store the results for analytics and visualization. How should you configure the pipeline? A. 1 = Dataflow, 2 = AI Platform...

Your organization wants to make its internal shuttle service route more efficient. The shuttles currently stop at all pick-up points across the city every 30 minutes between 7 am and 10 am. The development team has already built an application on Google Kubern...

You were asked to investigate failures of a production line component based on sensor readings. After receiving the dataset, you discover that less than 1% of the readings are positive examples representing failure incidents. You have tried to train several cl...

You want to rebuild your ML pipeline for structured data on Google Cloud. You are using PySpark to conduct data transformations at scale, but your pipelines are taking over 12 hours to run. To speed up development and pipeline run time, you want to use a serve...

You manage a team of data scientists who use a cloud-based backend system to submit training jobs. This system has become very difficult to administer, and you want to use a managed service instead. The data scientists you work with use many different framewor...

You work for an online retail company that is creating a visual search engine. You have set up an end-to-end ML pipeline on Google Cloud to classify whether an image contains your company's product. Expecting the release of new products in the near future, you...