Data Science & Artificial Intelligence Course

Overview

This intensive data science and artificial intelligence course covers technical training in essential core competencies for entry-level data science roles, including SQL, Python, and Python's data science libraries. The curriculum is intended to provide you with real-world training, so you acquire transferable skills that employers look for like SQL querying, automation, and data visualizations. The program also includes practical instruction in integrating AI models into web applications.

Through the practical exercises, you will gain valuable experience working to clean and visualize data, build machine learning models, develop dashboards using tools like Pandas, NumPy, scikit-learn, and build AI-powered web applications using Flask and OpenAI. This beginner-friendly machine learning course features capstone projects and practical assignments that prepare you for roles in data analytics, machine learning engineering, and AI.

The curriculum goes beyond basic data analytics by introducing you to back-end development and API integration using Python-based frameworks. You will learn to design and style user-facing web forms, make requests to AI platforms, and incorporate error handling into your applications. Upon completion of this artificial intelligence and data science course, you will be proficient in Python development tools and capable of building interactive, AI-enhanced web tools.
  • Course ID: GES3127
  • Total Hours: 260
  • Format: Asynchronous/Self-Paced
  • Location: Online
  • Schedule: 9 Months
  • Credit(s) Earned: 26 CEU
  • Instructor: Ed2go
  • Cost: $4,725.00
  • Category: Data Analytics
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Data Science & Artificial Intelligence Course

Prerequisites: 

Open to beginners; progresses to advanced topics. 

Requirements: 

Hardware Requirements: 

  • This course can be taken on either a PC or Mac. Chromebooks are not compatible. 

Software Requirements: 

  • PC: Windows 10 or later. 

  • Mac: macOS 12 or later. 

  • Browser: The latest version of Google Chrome or Mozilla Firefox is preferred. Microsoft Edge and Safari are also compatible. 

  • Microsoft Word Online 

  • Adobe Acrobat Reader 

  • Google Colab 

  • DBeaver 

  • Software must be installed and fully operational before the course begins. 

Other: 

  • Email capabilities and access to a personal email account. 

Instructional Material Requirements: 

The instructional materials required for this course are included in enrollment and will be available online. 

What You Will Learn

  • Study fundamental Python programming concepts like how to use its core data science libraries like NumPy and Pandas, read and write database queries, and automate routine data tasks 

  • Develop applications with AI that combine OpenAI's API into tools using Flask and HTML 

  • Work with data to create machine learning models and study their performance 

  • Use Python libraries like Seaborn, Dash, and Matplotlib to create dashboards and visualizations 

  • Learn how to structure API calls and render outputs in web-based applications using Python 

  • Explore PostgreSQL fundamental concepts, such as querying databases, applying aggregate functions, working with subqueries, and using joins to establish data relationships and merge the information contained in multiple tables 

Program Outcomes

  • Gain the practical training necessary to understand data science workflows and transition into machine learning 

  • Benefit from exploring how major companies like Spotify, Netflix, and Amazon leverage machine learning to tackle real-world problems 

  • Complete three final capstone projects in machine learning, artificial intelligence, and Python data visualization 

  • Understand how to publish completed projects to platforms like GitHub or Heroku to showcase your expertise to prospective employers