Text Analysis

About the course

Learn to leverage text analysis to grow your business. This two-day course will teach you to tackle unstructured pools of text and structure these for application in the analysis. Beginning with an introduction, we will follow all the steps to structure unstructured text data using different transformation methods such as DTM and TF-IDF, cleaning tools, and finally analyze the outcomes with basic and advanced analysis techniques. This is a practical hands-on course in which you will apply all theory to real cases performing text analysis. Moreover, we will pay special attention to transfer learning so you can work smarter, not harder, by transferring knowledge from pre-trained NLP models. Once completed, our Text Analysis training will arm you with the skills to have an immediate effect on your company, improve efficiency, and make predictions about the market.  

Why this is for you

We frequently see businesses that have the majority of their relevant data generated and stored in an unstructured written format. Most likely rendering it useless, meaning that there is a large amount of untapped potential waiting for your business. Our experts can help you utilize text analysis to transform this data to gain insights and make data-driven decisions on how to advance your organization.  

For whom

This training is great for Data Scientists who have previously completed our Machine Learning Process (3201) badge. Some techniques to analyze text such as LDA are quite technical, therefore, a basic level of mathematics and Python knowledge is required to fully grasp our training.  

What you’ll learn

1. An overview of the benefits and challenges of text analysis
2. Transformation methods including DTM and TF-IDF
3. Cleaning methods: tokenization, regular expressions, stop words, stemming, and spelling
4. Analysis methods: visualization and identification
5. Advanced analysis methods: clustering using LDA and transfer learning

Learning Goals

• Understand the text analysis landscape – Know the popular applications and typical challenges of text analysis
• Structuring unstructured data – Capable of following the required steps to structuring unstructured text data using different transformation methods
• Cleaning text data – Able to use different methods for data cleaning and explain when and when not to use these
• Basic analysis methods – Using a pragmatic toolbox to perform basic text description, clustering, and visualization
• Advanced analysis methods – Using sophisticated AI methods for automatic clustering and scoring of new documents

  Theory and practical use All trainings in the GAIn portfolio combine high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.