Data Analyst

The 200-hour, 8-week internship offers hands-on experience in a professional setting, enabling you to apply the knowledge and skills gained in the Data Analyst program. During the internship, you will gain industry experience, work on practical data analyst, and engage with professionals in the field. This practicum bridges the gap between classroom learning and career readiness.

This module builds on concepts and skills introduced in the Career Planning and Preparation Level 1 module. In this subsequent module, you will update and refine your résumé and LinkedIn Profile. You will continue writing cover letters and learn the value of customizing cover letters to specific job postings. You will have the opportunity to apply this knowledge as you conduct a job search and write a cover letter tailored to an ideal job post. Through research, you will create a list of top employers and target current industry opportunities. You will learn about current methods for applying to job postings using technology. You will also gain an understanding of the job interview process, typical interview questions and possible responses, and expectations of both the interviewer and interviewee. In addition, you will engage in practical application of the interview process through role-play. Topics such as negotiating salary, self-management, and on-the-job success for placements and post-graduate employment will be also covered.

This capstone course is designed to provide you an opportunity to apply your skills in data analysis, statistical methods, and data visualization to a substantial, real-world project. You will tackle a complex data problem, using advanced analysis techniques to uncover insights, build predictive models, and communicate findings through compelling visualizations. The focus will be on turning data into actionable insights for decision-making, and you will be expected to design and implement your analysis with careful attention to ethical issues, data integrity, and clarity in communication. At the end of the course, you will have a project that you can showcase to faculty, peers, and industry professionals.

In the rapidly evolving fields of data science and artificial intelligence (AI), professionals must not only possess strong communication skills but also navigate complex ethical challenges. This course explores ethics and communication in the practice of data analysis and AI development, equipping you with the tools to engage in responsible, transparent, and impactful work.

This course is designed to introduce you to the powerful tools and techniques available in Python for data analysis and visualization. You will learn how to collect, clean, and prepare data for analysis. Additionally, you will leverage the core Python libraries and techniques that form the foundation of data analysis, including Pandas for data manipulation, Seaborn for visualization, as well as the tools for building predictive models and presenting insights from data.

In this course you will learn the essential skills and techniques required to analyze and manipulate data using SQL, one of the most widely used languages for data management and analysis. More specifically, this course covers the full process of preparing, analyzing, and interpreting data using SQL. You will gain hands-on experience in structuring SQL queries, profiling data, cleaning and reshaping datasets, and performing advanced analytical tasks such as time series analysis, cohort analysis, and anomaly detection.

This course offers a thorough introduction to the statistical techniques essential for analyzing data and drawing meaningful conclusions. You will explore both the statistical methods commonly used in data analysis, including sampling distributions, hypothesis testing, regression analysis, classification, and statistical machine learning.

In this course, you will learn the principles and techniques of data visualization, a crucial skill for anyone working with data. Data visualization is not only about creating charts, but also about effectively conveying information and insights to audiences through compelling, informative visuals. This course will provide you with a comprehensive understanding of how to visualize data for both exploration and explanation, enabling you to create visuals that tell impactful stories, communicate insights effectively, and support informed decision-making.

This course introduces the fundamental concepts and principles of learning and working in a digital environment. This course will cover the following elements: using devices and handling information, creating and editing information, communicating and collaborating, and being safe and responsible online.

This course offers a comprehensive introduction to Python programming. In addition to core Python programming concepts, you will develop good programming practices, ensuring the programs are robust and reliable. By the end of the course, you will have gained the practical skills and theoretical understanding needed to effectively work with Python in future courses.

This course provides a comprehensive introduction to the fundamentals of SQL databases, focusing on the essential skills required to design, query, and manage relational databases. You will explore key concepts in database design, including how to create and structure tables to ensure efficient data storage and retrieval. By the end of the course, you will have gained the practical skills and theoretical understanding needed to effectively work with SQL data in future courses.

This course stresses the importance of developing non-technical skills to enhance personal, academic, and career success. The course will address strategies that are important for all adult learners, such as managing finances, maintaining health and wellness, understanding learning styles, setting goals, and honing practical study skills (such as memory, reading, and test-taking techniques). In addition, this course emphasizes strategies needed to succeed in your program, such as navigating technology efficiently, interacting and engaging with peers and facilitators/instructors, and managing learning time and space.