Artificial Intelligence & Machine Learning Course in Kochi, Kerala
Figmark offers a comprehensive Artificial Intelligence & Machine Learning Course in Kochi designed to help students and professionals build strong skills in data analysis, predictive modeling, and intelligent systems. This course covers essential Artificial Intelligence & Machine Learning concepts, algorithms, and practical implementation using Python, NumPy, Pandas, and Scikit-learn, enabling learners to work on real-world AI and data science projects.
About the course
Our Professional Artificial Intelligence & Machine Learning Course introduces students to the core concepts of Artificial Intelligence and data-driven decision making. Learners will gain practical experience in building machine learning models, analyzing datasets, and implementing predictive algorithms using Python-based tools and libraries.
This course focuses on both theoretical understanding and hands-on projects, helping students develop the skills required to pursue careers in Machine Learning, Data Science, Artificial Intelligence, and Analytics.
Introduction to the course
- Introduction to Machine Learning and Artificial Intelligence
- Working with Python for Data Science
- Data Analysis using NumPy and Pandas
- Data Visualization with Matplotlib and Seaborn
- Understanding Supervised and Unsupervised Learning
- Building real-world machine learning models
Syllabus
Introduction to Artificial Intelligence, History and Applications of AI, Types of AI Systems, AI vs Machine Learning vs Deep Learning, AI in Real-world Applications, Overview of AI Tools and Technologies.
Python Basics, Data Types, Control Statements, Functions, Object Oriented Programming, Working with Libraries such as NumPy, Pandas and Matplotlib, Data Manipulation and Analysis.
Data Collection, Data Cleaning, Handling Missing Data, Feature Engineering, Data Transformation, Data Visualization, Preparing Datasets for Machine Learning Models.
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Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Regression Algorithms, Classification Algorithms, Clustering Techniques, Model Training and Testing.
Introduction to Neural Networks, Artificial Neural Networks (ANN), Deep Learning Concepts, Introduction to TensorFlow and Keras, Model Building and Training.
Predictive Analytics Projects, Recommendation Systems, Image Recognition Basics, Natural Language Processing Basics, Real-world AI Applications and Project Development.