AI & ML Development

Jeel Borda

Quillix Founder

Provides expertise in developing intelligent systems using AI and Machine Learning.

AI & Machine Learning course introduces learners to intelligent systems, covering core concepts like data preprocessing, algorithms, and neural networks, providing a strong foundation in designing and implementing AI-driven solutions.

Students gain practical experience with tools like Python, TensorFlow, and scikit-learn, exploring applications in natural language processing, computer vision, and predictive analytics, preparing them to address real-world challenges using AI technologies.

Category

Development

Difficulty

Advanced

Videos

8 Modules

Time

02 Hours Daily

Assignments

Weekly Assignments
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The AI & Machine Learning course introduces learners to intelligent systems, covering core concepts like data preprocessing, algorithms, and neural networks. Students gain hands-on experience with tools like Python, TensorFlow, and scikit-learn, while exploring applications in natural language processing, computer vision, and predictive analytics. This program equips learners with the skills to design and implement AI-driven solutions for real-world challenges. The course structure is outlined as follows:

  • 1 Introduction to AI & ML:
    • • Recommended Tools: None (focus on theory and foundational concepts).
  • 2. Mathematics for Machine Learning
    • • Linear Algebra
    • • Probability & Statistics
    • • Calculus & Optimization
    • • Recommended Tools: MATLAB, NumPy (Python).
  • 3. Programming for AI & ML
    • • Python Programming
    • • Data Structures & Algorithms
    • • Recommended Tools: Python, Jupyter Notebooks, Anaconda.
  • 4. Data Preprocessing & Feature Engineering
    • • Data Cleaning, Transformation, and Visualization
    • • Feature Selection and Engineering
    • • Recommended Tools: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn.
  • 5. Supervised Learning
    • • Regression, Classification, and Decision Trees
    • • Recommended Tools: Scikit-learn, TensorFlow, Keras.
  • 6. Unsupervised Learning
    • • Clustering, Dimensionality Reduction, and Anomaly Detection
    • • Recommended Tools: Scikit-learn, TensorFlow, Keras.
  • 7. Neural Networks & Deep Learning
    • • Introduction to Neural Networks
    • • CNNs, RNNs, and LSTMs
    • • Recommended Tools: TensorFlow, Keras, PyTorch.
  • 8. Natural Language Processing (NLP)
    • • Text Processing, Language Models, and Sentiment Analysis
    • • Recommended Tools: NLTK, SpaCy, Hugging Face Transformers.
  • 9. Computer Vision
    • • Image Classification, Object Detection, and Image Generation
    • • Recommended Tools: OpenCV, TensorFlow, Keras, PyTorch.
  • 10. Model Evaluation & Tuning
    • • Cross-Validation, Hyperparameter Tuning, and Model Selection
    • • Recommended Tools: Scikit-learn, Hyperopt, Optuna.
  • 11. Deployment of AI & ML Models
    • • Model Serving, APIs, and Edge AI
    • • Recommended Tools: Flask, Docker, TensorFlow Serving, ONNX.
  • 12. Reinforcement Learning
    • • Markov Decision Processes, Q-Learning, and Deep Q-Networks
    • • Recommended Tools: OpenAI Gym, TensorFlow, PyTorch.
  • 13. Ethics & Fairness in AI
    • • Bias, Fairness, and Responsible AI Practices
    • • Recommended Tools: IBM AI Fairness 360, Google’s What-If Tool.
  • 14. AI & ML in Production
    • • MLOps, Model Monitoring, and Model Lifecycle Management
    • • Recommended Tools: MLflow, Kubeflow, AWS SageMaker.
  • 15. AI & ML Project Development & Portfolio Building
    • • Case Studies and Real-world Projects
    • • Recommended Tools: GitHub, Kaggle, Google Colab.
Course Introduction

This course introduces core concepts of AI, including algorithms and neural networks, while providing hands-on experience with tools like TensorFlow and Python to solve real-world problems.

  • Written Material
    5 Documents
  • Video Material
    8 Modules
  • Assignment material
  • Quiz
    20 Questions
Jophie Alen
★★★★★

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Jophie Alen
★★★★★

Lorem ipsum dolor sit amet consectetur. Non convallis sed id aliquam tempus. Volutpat tortor tincidunt egestas sit risus donec.

Jophie Alen
★★★★★

Lorem ipsum dolor sit amet consectetur. Non convallis sed id aliquam tempus. Volutpat tortor tincidunt egestas sit risus donec.

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