Post Graduate Program in Data Science, Generative AI & Cloud Computing (Live Online)

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About Course

The Post Graduate Program in Data Science & Generative AI is a cutting-edge program designed to equip learners with expertise in Data Science, Artificial Intelligence, and Generative AI. This comprehensive course provides hands-on experience with real-world projects, covering essential concepts like Machine Learning, Deep Learning, Natural Language Processing, and Cloud-based AI solutions. Whether you are a fresh graduate or a working professional, this program ensures career growth in the rapidly evolving AI landscape.

 

Why Choose the PG Program in Data Science and AI?

Career Opportunities After the Program

Graduates of this program will be prepared for various high-demand roles, including:

  • Data Scientist Analyze and interpret complex data to drive business insights.

  • Machine Learning Engineer – Develop and deploy machine learning models to solve real-world problems.

  • AI Research Scientist – Conduct research and innovate in the field of Artificial Intelligence.

  • Big Data Engineer – Work with large-scale data processing frameworks such as Hadoop and Spark.

  • Cloud AI Engineer – Deploy AI solutions using cloud platform like Azure.

  • Business Intelligence Analyst – Utilize data visualization tools like Power BI and Tableau to extract actionable insights.

  • Data Engineer – Design, build, and maintain scalable data pipelines for businesses.

  • NLP Engineer – Develop AI solutions for text analysis, chatbot development, and voice recognition.

  • Deep Learning Engineer – Work on advanced AI models such as CNNs, RNNs, and Transformer networks.

  • MLOps Engineer – Automate machine learning workflows and manage model deployment.

With the rapid expansion of AI and data-driven industries, graduates can expect strong job prospects and opportunities for career advancement in various sectors, including finance, healthcare, e-commerce, marketing, and technology.

Roles Offered

8-in-1 Learning Excellence with KAE Education

 

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Sample Certificate

 

Post Graduate Program in Data Science, Generative AI & Cloud - Sample Certificate

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What Will You Learn?

  • Master SQL & NoSQL databases for efficient data manipulation and querying.
  • Gain expertise in Python & R programming for data analysis and machine learning.
  • Understand statistical concepts & hypothesis testing for data-driven decision-making.
  • Learn Machine Learning algorithms like Decision Trees, Random Forest, and SVM.
  • Explore Deep Learning & Generative AI using TensorFlow, Keras, and BERT.
  • Develop skills in Natural Language Processing (NLP) for text analytics and chatbot development.
  • Work with Big Data tools like Apache Spark, Hadoop, and PySpark for large-scale data processing.
  • Implement Cloud Computing & MLOps on Azure for scalable AI deployment.
  • Create dynamic Data Visualizations using Power BI or Tableau for insightful analytics.
  • Build an end-to-end Capstone Project applying Data Science, AI, and Cloud concepts.

Course Content

Module 1. SQL (RDBMS / NoSQL)

  • SQL Manipulations (DDL, DML, DQL)
  • SQL Joins
  • String, Mathematical & Date-Time Functions
  • NoSQL Databases & Querying

Module 2. Data Science with Python

Module 3. Data Science with R

Module 4. Statistics for Machine Learning

Module 5. Mathematics Foundation for AI & ML

Module 6. Machine Learning (ML)

Module 7. Exploratory Data Analysis (EDA)

Module 8. Clustering & Dimensionality Reduction

Module 9. Association Rules & Recommendation Engine

Module 10. Text Mining & Natural Language Processing (NLP)

Module 11. Advanced Machine Learning Techniques

Module 12. Hypothesis Testing & Confidence Intervals

Module 13. Regression Techniques

Module 14. Time Series Forecasting & Survival Analytics

Module 15. Machine Learning Model Evaluation & Deployment

Module 16. Deep Learning & Generative AI

Module 17. Model Deployment & MLOps

Module 18. Cloud Computing for AI & Data Science

Module 19. Power BI & Tableau for Data Visualization

Module 20. Capstone Project

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