LAW: Business Plan ( Photographer)

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Domestic Business Plan ( Photographer)

As an entrepreneur, you want to start a business. You know that the first step is to consider drafting a business plan to organize all of your ideas. For this assignment, you will be submitting a business plan for your imaginary business. For research purposes, you can choose any state for the location of your business. Your business plan should include the following:

Introduction of the proposed business/executive summary

oThe executive summary is often considered the most important section of a business plan. This section briefly tells your reader where your company is, where you want to take it, and why your business idea will be successful. If you are seeking financing, the executive summary is also your first opportunity to attract a potential investor’s interest.

oThe executive summary should highlight the strengths of your overall plan and therefore be the last section you write. However, it appears first in your business plan.

Identify and describe the type of business entity that is best for your business.

oExamples may include: partnership, limited liability company, corporation, etc. (For purposes of this assignment, you should NOT choose a sole proprietorship for your business entity.)

oDefend your choice of business entity (this may include advantages/disadvantages of the selected type of business entity based on your business concept).

Describe the specific legal steps needed to be followed to successfully start the business.

oNote: Steps will vary, depending on the type of business you choose and state you are located in.

oGood sources of research for this area include the following:

§Textbooks

§Information on the business formation process can be found at: http://smallbusiness.findlaw.com/incorporation-and-legal-structures/business-formation-quickstart.html (Links to an external site.). The Small Business Administration website will be helpful; it includes information on how to start a small business.

Recommend and describe an appropriate written agreement for the particular type of entity chosen.

oExamples: Articles of incorporation, articles of organization, partnership agreement, etc.

A draft of a valid contract with a vendor, supplier, customer, etc. that illustrates all elements of a contract and takes into consideration some of the topics discussed in Modules 6 and 7

Explain potential ethical considerations for your business, including any social responsibility plans or attitudes that your business will embrace.

Describe a possible disagreement that could be encountered among the partners or investors and shareholders. Recommend potential resolutions (referring back to the formal documents, such as the articles of incorporation or the partnership agreement).

oExamples could include the introduction of a new product line, borrowing money for expansion, an advertising campaign, etc.

Determine how the business would be terminated if the disagreement between the board of directors, shareholders, or partners could not be resolved.

Your well-written plan should be 8-10 pages in length, not including the title or references pages. Headings and subheadings may help you organize your work. Include at least four academic or other legitimate sources to support your findings, not including your textbook. The MGT315 Business Law Library Guide (Links to an external site.) can help you with finding quality resources.

Review the Portfolio Project grading rubric, and make sure to follow the CSU-Global Guide to Writing & APA (Links to an external site.). Please be sure to reach out to your instructor at any point in the course if you have questions about the assignment.replies-ERM and data science
I don’t understand this Computer Science question and need help to study.

Main que:What is Data Science? What is the difference between Data Science, Big Data and Data Analytics? How does Machine Learning relate to this? What is the difference between Machine Learning and Statistical Learning? What is the difference between AI i.e. Artificial Intelligence and Machine Learning?

Provide replies to below student posts each in 150 words.2 student posts.

Rame:The amount of data in the modern world is overgrowing, changing how people live as well as how scientists conduct researches. Data seems everywhere. As digital data increases, various concepts have emerged. Notably, many people use multiple data concepts interchangeably. Therefore, understanding the different methods associated with data is vital.

Data science, big data, and data analytics are the first concepts to consider. Data science involves the actual activities that deal with both structured and unstructured data. The field encompasses all practices associated with the preparation, cleansing and analyzing data (Agarwal & Dhar, 2014). In contrast, Big data is the large volume of information that scientists cannot process effectively through traditional approaches. Subsequently, Data analytics entails the actual science of evaluating raw data to produce particular concrete finished information (Agarwal & Dhar, 2014). The differences in data science, big data and analytics enhance machine learning succeed. Machine learning can never be effective without the three concepts.

Machine learning and statistical learning also confuses many people. Usually, it is always hard to differentiate the two terms due to how people view data science. Notably, the two concepts are dependent. Nonetheless, statistical learning focuses on rule-based programming. Statistical learning relies on various variables. In contrast, machine learning studies data without any programmed instructions (Hothorn, 2019). Moreover, statistical learning depends on assumptions such as homoscedasticity and normality. Conversely, machine learning does not operate on-premises (Hothorn, 2019). Equally, statistical learning is more math-intensive, while machine learning focuses on identifying patterns of the set data.

It is also fundamental to examine the difference between artificial intelligence and machine learning. Artificial intelligence refers to human knowledge. The concept comprises of complex machines and computers that act like human beings. Conversely, machine learning is typically a section of artificial intelligence (Ghahramani, 2015) Machine learning uses algorithms to learn, get and analyze data. Thus in a nutshell, machine learning is the method of machines studying data from various analyses to make artificial intelligence succeeds.

Naga:Data Science is an interdisciplinary way to deal with information science. It lies at the crossing point of math, insights, man-made brainpower, plan thinking and programming building. Data Science is worried about information assortment, cleaning, investigation, perception, model development, model approval, expectation, analyze structure, speculation testing, and the sky is the limit from there. Every one of these moves are planned for picking up knowledge.

Differernce:Data Science is the blend of insights, arithmetic, programming, critical thinking, catching information in clever ways, the capacity to take a gander at things in an unexpected way, and the action of preparing, and aligning the data.

Big Data used to describe immense volumes of data, both unstructured and structured, Big Data inundates a business on a day-to-day basis. Big Data is something that can be used to analyze insights that can lead to better decisions and strategic business moves.

Data Analytics is used in many industries to enable better decision-making by organizations and companies as well as to validate and disprove existing theories or models. Data Analytics focuses on inferencing, which is the process of drawing conclusions based solely on what the researcher already knows.

What is the difference between Machine Learning and Statistical Learning?Data Science is the blend of insights, arithmetic, programming, critical thinking, catching information in clever ways, the capacity to take a gander at things in an unexpected way, and the action of preparing, and aligning the data.Machine learning promotes data science by offering a collection of algorithms for data modeling / analysis (through training of machine learning algorithms), decision-making and even data preparation.

When Machine Learning comes to life and moves beyond simple programming and can reflect and interact with people, even on the most basic level, this is where AI comes into play. AI is evolving. We are currently perceiving that most things called “computer based intelligence” in the past are just best in class programming stunts. For whatever length of time that the developer is the one providing all the knowledge to the framework by programmingYour Approach to Hiring is all Wrong”, by Cappelli, Peter. Harvard Business Review. May/Jun2019, Vol. 97 Issue 3, p48-58.: assignment help online
I don’t understand this Management question and need help to study.

Download the article, read it carefully and answer the following questions. Also use at least 2-3 additional scientific references to support your answers/opinions.
Assignment Questions:
Summarize the article in your own words. (minimum of 250 words).[Marks:2] Reliance on data science in the hiring process, is this critical to the desired outcome? Describe this is no less than 100 words.[Marks: 2] Discuss why employers find the hiring process difficult? Make some suggestions to develop such a recruitment process which can hire the best employees for the organization. [Marks: 1]

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