Data mining has a rich history of unearthing hidden connections and unlocking future trends. This process, also known as “knowledge discovery in databases,” is made possible by the convergence of statistics, artificial intelligence, and machine learning. These intertwined disciplines allow us to analyze, capture, search, share, store, transfer, visualize, query, and update massive and complex data sets in real-time, thereby avoiding losses due to fraud, waste, or revenue loss.
At TripleJ Consulting, we understand the value of Big Data and the challenges that companies face when trying to leverage it effectively. That’s why we offer an introductory data science course designed specifically for non-data science professionals. Our training covers the methodology, concepts, and tools used in data science, including Machine Learning, Artificial Intelligence, Deep Learning, Automation, and Statistics.
By taking our course, you’ll gain a comprehensive understanding of these methodologies and be able to apply them to your business. You’ll also learn about the tools used for each concept, along with their similarities and differences. This newfound knowledge will allow you to make informed decisions about how digitalization can enhance your business and which areas to focus on.
Whether you’re a business owner, executive, project manager, agile coach, business analyst, data analyst, or in any other role related to data science, our training will equip you with the skills to engage with data science professionals in intelligent conversions. You’ll be able to work on data science projects confidently and contribute meaningfully to your organization’s growth and success.
As a result of taking this course, you will be able to:
- Understand the techniques and evolution of data science
- Understand the fundamentals of Data Science
- Statistical concepts and methodologies backing data science
- The similarities and variances within these methodologies
- Understand what data science does for you and how you can leverage it
- The optimal goal and how to make it work for your bottom line
- The relationship between data science and data analytics
- Understand Machine learning, deep learning and artificial intelligence