Cybersecurity

Data Analyst Core & Professional Skills

Data analysts are critical thinkers who use their abilities to obtain insight from data to resolve technical real-life problems. Core skills for data analysts include using prescribed analytical techniques and tools to collect, clean, manage, and analyze data; identifying insights to solve business problems; and visualizing data to successfully communicate results in a clear way to stakeholders.

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Core skills for data analysts include using prescribed analytical techniques and tools to collect, clean, manage, and analyze data; identifying insights to solve business problems; and visualizing data to successfully communicate results in a clear way to stakeholders. Data analysts have prerequisite knowledge in basic mathematics and statistics as well as business acumen. Along the way, you’ll deep dive into ways that AI makes predictions, understands language and images, and learn using circuits inspired by the human brain. After a hands-on simulation in which you build and test a machine learning model, you’ll finish with tips on how to find your own career in artificial intelligence.

 

What you’ll learn

  • Describe fundamental data concepts including types of data, big data, analytics techniques, typical steps in the data analytics process, and data visualization

  • Identify widely adopted data science methodologies and explain the activities in a typical data science project

  • Identify applications of data science across industries in the world

  • Describe the role of a data analyst, data scientist, and data engineer

  • Identify the purpose and use of some common data analysis and visualization tools

  • Clean, refine, and visualize data using IBM Watson Studio with the data refinery tool

  • Recognize the job market, responsibilities and skill sets of a data analyst and data scientist, and resources and learning opportunities to explore

  • Define and describe structured and unstructured data, machine learning, and ways that AI makes predictions from data

  • Explain how AI understands human language & how AI analyzes and creates images

  • Describe how AI makes predictions using neural networks

  • Create an AI machine learning model using IBM Watson Studio

  • Describe ways that AI systems can be designed to minimize bias

  • Recognize the AI job market, responsibilities and skill sets of an AI professional, hand resources and learning opportunities to explore

 

  • Approximate Duration: 50 Hours

Upcoming Course Dates

  • December 12th 2024

Get certified in

  • Data & AI Fundamentals

Course Level

  • Beginner

Venues

  • Remote

Prerequisites

  • None Required

Schedule

  • Remote
    • Asynchronous/Self-paced: Learners are utilizing a platform for self-paced learning with structured office hours/workshop support; Still has a start and end date, but may be loose. For example Google offerings via Coursera: Python, Data Analytics, Project Mgmt; IBM Skillsbuild
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Have questions?

We can help with course selection, and answer questions about eligibility requirements and special circumstances. Contact an Alumni Admissions team member