AI for Big Data Analytics Course

In this data-driven decision-making era, the efficient analysis and interpretation of large volumes of data can be a very important factor. The “AI for Big Data Analytics” course by Oxford Training Centre gives a deep insight into how Artificial Intelligence techniques can be applied in Big Data environments. This one-week course aims to equip professionals with practical skills and knowledge to leverage AI tools and methodologies for extracting valuable insights from complex data sets.
The course covers subjects such as machine learning, deep learning, natural language processing, and data visualization, all in terms of how to use these technologies to drive decisions. The course provides a blend of theoretical knowledge and practical experience; the course provides real-world applications and a comprehensive project to tie everything together.

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Objectives and target group

Objectives

The primary goal of this course is to enable participants to integrate AI methods into Big Data analytics, improving their ability to extract actionable insights and drive strategic decision-making. The objectives are:

  • Understand the core principles of AI and its role in Big Data analytics.
  • Apply machine learning and deep learning techniques to analyze large datasets.
  • Use AI-driven tools for predictive analytics and business intelligence.
  • Gain proficiency in natural language processing (NLP) for text-based Big Data analysis.
  • Learn how to preprocess and clean data for optimal AI analysis.
  • Utilize data visualization tools to present AI-driven insights effectively.
  • Develop a strong understanding of AI algorithms and how they can be used for automated decision-making.
  • Complete a hands-on project to apply the learned concepts to real-world Big Data scenarios.

Target Group

The course is suitable for:

  • Data Analysts looking to gain advanced knowledge of AI techniques.
  • Data Scientists seeking to enhance their skills in Big Data analytics using AI.
  • Business Intelligence Professionals aiming to incorporate AI into their analytical workflows.
  • IT Professionals interested in implementing AI-driven solutions within Big Data systems.
  • Managers and Executives who want to understand AI’s role in data-driven decision-making.
  • Anyone pursuing a career in AI and Big Data Analytics.

Course Content

The course covers a wide range of topics, structured to provide both theoretical insights and practical experience. Key modules include:

1. Introduction to AI and Big Data

Big Data and AI principles overview: Looks into how AI enhances Big Data analysis. Participants learn why AI is important, its applications, and how it fits into the data analytics domain.

2. Data Preprocessing and Exploration

This module will look into the very important step of preparing data for AI analysis. Techniques of data cleaning, normalization, transformation, and exploration will be taught to optimize it for machine learning.

3. Machine Learning for Big Data

Participants will learn about supervised and unsupervised learning, algorithms comprising decision trees, regression models, clustering, and classification techniques, which are fundamental in analyzing large datasets.

4. Deep Learning and Neural Networks

The module looks at advanced AI techniques, deep learning, with neural networks, convolutional networks, and recurrent networks, which can be used for Big Data in more complex analysis.

5. Natural Language Processing (NLP) for Text Analytics

One of the big components of Big Data, unstructured text will be investigated using NLP techniques. Students will apply methods like sentiment analysis, text classification, and language modeling to analyze and interpret textual data.

6. Data Visualization and Reporting

Presenting insights will depend on good data visualization. The module will discuss how tools such as Tableau and Power BI can be used to design powerful dashboards and reports for stakeholders that tell a story using AI-driven insights.

7. AI for Predictive Analytics

Use AI for prediction of future trends, customer behavior, and business outcomes; how to apply and evaluate predictive models for actionable purposes.

8. Practical Project and Case Study

The course culminates in a hands-on project where learners apply AI techniques to a real-world Big Data scenario. This final project helps solidify learning and provides an opportunity to demonstrate the ability to use AI for business intelligence.

Course Dates

January 27, 2025
February 10, 2025
March 24, 2025
April 21, 2025

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