Putting it Together - Data Science for AI Applications

This AI and data science course is ideal for aspiring data scientists, AI professionals, recent graduates, and IT or software developers looking to transition into AI and data-driven roles. Data analysts seeking hands-on experience in predictive and AI applications will also benefit.

Learners should have prior knowledge of Python programming for data analysis, SQL basics for data retrieval, machine learning fundamentals (classification, regression, evaluation metrics), and familiarity with data visualization tools such as Excel, Tableau, or Cognos.

This data science with artificial intelligence course covers data preparation with SQL and Python, feature engineering, model building with TensorFlow, data visualization with Tableau, Cognos, or Excel, and AI model deployment using Flask, FastAPI, Git, and Azure. Youll also practice the full AI lifecycle with hands-on labs.

Yes. The highlight of this data science and AI online course is a capstone project where you design and deliver an end-to-end AI application, such as churn prediction, sentiment analysis, or image classification, demonstrating your practical AI skills.

You will develop AI applications in areas like customer churn prediction, sentiment analysis, and image classification. These AI Applications in data science give hands-on experience with real-world problem solving, model evaluation, and visualization.

The course is instructor-led and organized into eight modules covering the AI lifecycle, data preparation, feature engineering, machine learning and deep learning with TensorFlow, visualization, model deployment, and the capstone project. Each module includes live sessions, labs, knowledge checks, and guided exercises.

Yes. Youll gain practical experience in building and evaluating both machine learning and deep learning models using TensorFlow, preparing you for advanced AI applications and real-world project deployment.

Data preparation is done using SQL and Python, including feature engineering techniques. Visualization of predictions and insights is performed using Tableau, Cognos, or Excel dashboards, enabling clear and interactive reporting of model results.

Yes. Youll learn how to deploy AI models using Flask or FastAPI, manage versioning with Git, and perform basic deployment on Azure. This ensures practical experience in delivering production-ready AI solutions.

Absolutely. This AI and data science course include extensive hands-on labs and exercises in SQL, Python, and TensorFlow. Youll practice data cleaning, model building, evaluation, visualization, and deployment throughout the course.

The end-to-end capstone project allows learners to showcase a complete AI application. Completing this data science with artificial intelligence project equips you with a portfolio-ready artifact that demonstrates real-world problem-solving and AI application skills to potential employers.

Yes. Knowledge checks, graded exercises, and quizzes are integrated to assess understanding and reinforce practical skills throughout this AI and data science online course.

Yes. Upon completion of this artificial intelligence with data science course, you receive a Certificate of Completion, demonstrating mastery of data science and AI skills, including end-to-end project execution.

By completing this AI applications in data science course, you gain practical, hands-on experience in preparing data, building models, visualizing insights, deploying solutions, and delivering portfolio-ready projects all skills that make you job-ready for AI and data science roles.