AI/ML TRAINING
Requirements
- Basic Programming Knowledge – Familiarity with Python is recommended but not mandatory.
- Mathematics & Statistics Fundamentals – Understanding of linear algebra, probability, and statistics is helpful.
- Basic Understanding of Data Structures – Knowledge of arrays, lists, and basic algorithms is beneficial.
- Logical Thinking & Problem-Solving Skills – Ability to analyze and solve complex problems.
- System Requirements – A computer with Python, Jupyter Notebook, and essential libraries (NumPy, Pandas, Scikit-learn) installed.
Features
- Comprehensive Curriculum – Covers Python, Machine Learning, Deep Learning, and AI concepts.
- Hands-on Projects – Work on real-world datasets and AI applications.
- Industry-Standard Tools – Learn TensorFlow, PyTorch, Scikit-learn, Pandas, and more.
- Model Deployment & Optimization – Train, evaluate, and deploy ML models in production.
- Certification & Career Support – Earn a certificate and receive job placement assistance.
Target audiences
- Aspiring Data Scientists & ML Engineers – Individuals looking to start a career in AI and Machine Learning
- Software Developers & Engineers – Professionals wanting to integrate AI/ML into applications.
- Data Analysts & Statisticians – Those aiming to enhance their skills with predictive modeling and automation.
- IT Professionals & Career Switchers – Individuals transitioning into AI/ML from other tech fields.
- Entrepreneurs & Researchers – Business owners and academics interested in leveraging AI for innovation.
Course Description
The AI/ML Training course is designed for professionals and students who want to gain expertise in Artificial Intelligence (AI) and Machine Learning (ML)
- Introduction to AI/ML
- Python for AI/ML (Numpy, Pandas, Matplotlib, Scikit-learn)
- Data Preprocessing & Feature Engineering
- Supervised Learning (Regression & Classification Models)
- Unsupervised Learning (Clustering & Dimensionality Reduction)
- Deep Learning & Neural Networks with TensorFlow/Keras
- Natural Language Processing (NLP) & Computer Vision
- Deploying AI/ML Models (Flask, FastAPI, Cloud Services)
Basic Python knowledge is recommended, but foundational programming concepts will be covered.
You will work with Python, NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, and AI/ML model deployment techniques.
Yes, you will get a certification upon successfully completing the training.
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