They always say that the data never lies...but is that true? Our bet is it depends on the analyst. In this WorkMYX, you will learn all the skills necessary to become an excellent data analyst. Anchored in the IBM Data Analyst Professional Certification Program, you will learn the core principles of data analysis and gain hands-on skills practice. You’ll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics. The best part? We don’t stop there. At MYX, we aim to create a more ethical world. We don’t want you to just be a killer data analyst, we want you to be an ethical killer data analyst. This WorkMYX is a home run for your career and you’ll never have to sell your soul to the data.
#1 in CNN analysis of “Careers with Big Growth, Great Pay and Satisfying Work," (source: cnn.com)
Employment of software developers is projected to grow 24% from 2016 to by 2026, much faster than the average for all occupations. (source: Occupational Outlook Handbook)
Ronald Van Loon, Craig Brown, Bob Hayes
Average Salary $97,100. Entry level $58,000 (source: PayScale.com)
Apps can allow people to connect, be more efficient, and learn. They can also create distractions, bad habits, and lead to isolation. What will your impact be?
BS degree in data analytics
Gain the job-ready skills for an entry-level data analyst role through this eight-course Professional Certificate from IBM and position yourself competitively in the thriving job market for data analysts, which will see a 20% growth until 2028 (U.S. Bureau of Labor Statistics). Power your data analyst career by learning the core principles of data analysis and gaining hands-on skills practice. You’ll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining practical experience with data manipulation and applying analytical techniques.
This Professional Certificate does not require any prior programming or statistical skills, and is suitable for learners with or without college degrees. All you need to get started is basic computer literacy, high school math, comfort working with numbers, willingness to learn, and a desire to enrich your profile with valuable skills. Upon successful completion of this program, you’ll have analyzed real-world datasets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and the portfolio to begin a career as an associate or junior data analyst. You’ll also build the foundation for other data disciplines such as data science or data engineering.
Demonstrate proficiency in using spreadsheets and utilizing Excel to perform a variety of data analysis tasks like data wrangling and data mining
Create various charts and plots in Excel & work with IBM Cognos Analytics to build dashboards. Visualize data using Python libraries like Matplotlib
Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services
Describe data ecosystem and Compose queries to access data in cloud databases using SQL and Python from Jupyter notebooks
In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.
Explore fundamental issues of fairness and bias in machine learning
Ethics in data analytics
Data bias and building more ethical models
Do you remember when you first created your Facebook account? Do you know what happens to the data and stories you share on Facebook? Are you aware of the Facebook – Cambridge Analytica crisis and its ramifications?
In this course, you will take a deep dive into reputation management by tackling a case study on the crisis, the effects of which are still unravelling for Facebook, the tech industry, and society at large. You will explore the concept of corporate reputation, and touch upon topics such as data privacy implications for the big tech or the importance of leadership and culture, and how Mark Zuckerberg’s leadership might have affected Facebook in particular. In the final project, you will be asked to link theory and practice to provide an analysis of events and make recommendations for Facebook, going forward.
This 6-module course has a study time of about 20 hours. It is recommended for anyone studying communication or management, practitioners interested in crisis and reputation management, or anyone with an interest in case learning that explores real-life business challenges. Each week, you will be introduced to engaging content, such as videos, quizzes, discussion forum, and academic readings, and be encouraged to apply learned knowledge to the case. The final module – the capstone project – is assessed by peer review.
Analyse the challenges of reputation management in the digital age
Understand the role and relevance of counter-institutional mechanisms, such as whistleblowing, to check corporate power and influence
Examine the interaction and nexus of politics and business and their ethical and societal consequences
Analyse how large tech companies manage or reconcile the paradox between commercial and societal interests
What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches?
This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."
This course will help you answer questions such as who owns data, how we value privacy, how to receive informed consent and what it means to be fair.
What are ethics and how do we value privacy?
The history and concept of informed ethics
Data ownership and privacy
Algorithmic fairness and societal consequences
In this course you will engage in a series of challenges designed to increase your own happiness and build more productive habits. As preparation for these tasks, Professor Laurie Santos reveals misconceptions about happiness, annoying features of the mind that lead us to think the way we do, and the research that can help us change. You will ultimately be prepared to successfully incorporate a specific wellness activity into your life.
This work totals 180 hours over the course of 15 weeks
Please note that MYX will enroll you in these courses before the start of term.