Prerequisite

Basic Programming Knowledge

While not essential to be an expert programmer, familiarity with at least one programming language such as Python, Java, or R is required. Understanding basic programming concepts like variables, loops, and functions will be beneficial for grasping AI and ML concepts

Good Analytical Skills

A strong foundation in analytical thinking is essential for understanding and solving complex problems in AI and ML. The ability to break down problems, identify patterns, and analyze data critically will be key to success in the course.

Willingness to Learn

AI and ML are dynamic fields that require continuous learning and adaptation to new technologies and techniques. A proactive attitude towards learning, openness to new ideas, and eagerness to explore emerging trends will be crucial for staying updated and excelling in the course.

Mathematics Fundamentals

While not explicitly mentioned, having a basic understanding of mathematics concepts such as algebra, calculus, probability, and statistics will greatly aid in comprehending AI and ML algorithms and methodologies.

Problem-Solving Skills

The ability to approach problems systematically, devise creative solutions, and troubleshoot issues effectively is vital for AI and ML development. Strong problem-solving skills will enable you to tackle real-world challenges and develop innovative AI solutions.

Course Roadmap

Here's a month-by-month roadmap for the course

This structured roadmap ensures that participants gradually build upon their skills, starting from the basics of programming and gradually progressing towards advanced concepts in AI and ML. The hands-on projects in the later months provide valuable practical experience and prepare participants for real-world challenges in the field of AI and ML development.

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Month 1 - Basic Python and Programming Fundamentals:
  • Introduction to Python programming language.
  • Understanding variables, data types, and basic operators.
  • Control flow statements: if, else, loops.
  • Functions and modules in Python.
  • Basic data structures: lists, tuples, dictionaries.
  • Introduction to object-oriented programming (OOP) concepts.
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Month 2 - Web Development Fundamentals and AI/ML Introduction:
  • HTML and CSS basics for building web pages.
  • Introduction to JavaScript for client-side scripting.
  • Basics of responsive web design.
  • Introduction to web frameworks like Flask or Django.
  • Building simple web applications and understanding HTTP protocols.
  • Understanding API Development
  • Introduction to Artificial Intelligence and Machine Learning.
  • Data Analysis libraries like Pandas, NumPy
  • Data Visualization libraries like Matplotlib, Seaborn
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Month 3 - AI/ML Fundamentals:
  • Understanding of Neural Networks and Activation Functions
  • Understanding supervised and unsupervised learning.
  • Fundamentals of Computer Vision
  • Overview of popular ML libraries like TensorFlow or Scikit-learn.
  • Introduction to data preprocessing and feature engineering.
  • Introduction to platforms like OpenAI, Hugging Face, Kaggle and their applications
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Month 4 - Model Training and Sample Project Execution:
  • Data collection, processing and cleaning.
  • Exploring various ML algorithms: regression, classification, clustering .
  • Hands-on training on model building, evaluation, and optimization.
  • Understanding model selection and hyperparameter tuning.
  • Implementing sample projects to reinforce learning.
  • Introduction to deep learning and neural networks.
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Months 5-6 - Real-time Project Execution based on Skills Learned:
  • Working on real-world projects to apply skills learned in previous months. .
  • Collaborative project work in teams to simulate real industry scenarios.
  • Implementing end-to-end ML solutions from data preprocessing to model deployment.
  • In-depth analysis of project outcomes and presentation of findings.
  • Mentoring and guidance provided by industry experts throughout the project duration.

This structured roadmap ensures that participants gradually build upon their skills, starting from the basics of programming and gradually progressing towards advanced concepts in AI and ML. The hands-on projects in the later months provide valuable practical experience and prepare participants for real-world challenges in the field of AI and ML development.