Workshop detalis

Data Science With AI

Workshop: 2-3days
Polytechnic: CSE
Enrolled: 60 students
(30 Reviews)

Data Science and AI combine statistical analysis, programming, and machine learning to extract valuable insights from data and create intelligent systems. Data Science focuses on collecting, cleaning, and analyzing data, while AI uses algorithms and models to mimic human intelligence, enabling tasks like prediction, classification, and automation. Together, they drive innovation in industries such as healthcare, finance, marketing, and manufacturing.

These technologies empower organizations to make data-driven decisions, improve efficiency, and enhance customer experiences. With tools like Python, R, TensorFlow, and cloud-based AI services, professionals can develop solutions ranging from chatbots and recommendation systems to predictive analytics and autonomous systems, shaping the future of business and technology.

Course description

This Data Science and AI course covers the fundamentals of data analysis, machine learning, and artificial intelligence. It teaches data collection, preprocessing, visualization, and model development using tools like Python, Pandas, and TensorFlow.

What you'll learn from this course
  • Understand core concepts of Data Science, Machine Learning, and AI.
  • Collect, clean, and analyze data using Python and relevant libraries.
  • Build and train machine learning models for predictions and classifications.
  • Apply AI techniques such as natural language processing and computer vision.
  • Deploy AI-powered solutions for real-world business and industry use cases.
Certification

At TechIn IT, we proudly assure that every Trainee who successfully completes our program will be awarded a certificate. We are officially associated with APSCHE, AICTE, MSME, Skill India, IAF, and NASSCOM. The certification will reflect the Trainees dedication and skill development, recognized under national-level standards .

  • Fundamentals of Data Science and AI

    Introduction to data science concepts, workflows, and applications.

    Basics of artificial intelligence and its real-world impact.

    Understanding machine learning types: supervised, unsupervised, and reinforcement learning.

  • Tools, Technologies, and Techniques

    Working with Python, Pandas, NumPy, and visualization libraries.

    Introduction to AI frameworks like TensorFlow and PyTorch.

  • Applications and Deployment

    Building predictive and classification models for business needs.

    Implementing AI in natural language processing and computer vision.

    Deploying and integrating AI solutions into real-world systems.

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