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Technology & IT
Artificial Intelligence with python
Learn from : Nagasri P
Python, SQL (MySQL, Statistical Analysis, Statistics for data analysis, Machine Learning, Deep Learning, NLP, CNN, R Programming, Artifical intelliiegence
Course Language: English
Course Fee
$273.00
Course Fee
$273.00
Instructor Bio:
Experienced Data Science Trainer with over 8 years of expertise in delivering hands-on training across industries and academic institutions. Specialized in Python, Machine Learning, Deep Learning, and Data Visualization tools such as Power BI and Tableau. Fluent in English and Tamil, with the ability to conduct sessions effectively in both languages to cater to diverse learner groups. Proven track record of designing customized training programs aligned with industry standards and learner needs. Strong communication skills, adept at simplifying complex concepts for learners at all levels.
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Course Description:
Artificial Intelligence (AI) Course Description
Course Title: Introduction to Artificial Intelligence
Duration: 40-60 hours (can be customized for beginner, intermediate, or advanced levels)
Delivery Mode: Online / Offline / Blended
Prerequisites: Basic knowledge of programming (preferably Python), mathematics (linear algebra, probability), and data structures
Course Curriculum:
Module 1: Neural Networks
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Introduction to Neural Networks and Deep Learning
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Activation Functions
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Feedforward Neural Network
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Backpropagation and Gradient Descent
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Learning Rate Setting and Tuning
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Introduction to Keras
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Fully Connected Layer – Forward and Backward Pass
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Softmax and Cross-Entropy Loss
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Data Preprocessing
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Data Augmentation
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Weight Initialization
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Regularization – Batch Normalization
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Regularization – Dropout
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Working with Google Colab
Module 2: Convolutional Neural Networks (CNN)
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Introduction to CNNs
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Convolution Operation
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Pooling Layers
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CNN Architectures – LeNet, AlexNet, VGG
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Transfer Learning with CNN
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Implementing CNN with Keras/TensorFlow
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CNN Use Cases – Image Classification, Object Detection
Module 3: Natural Language Processing (NLP)
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Introduction to NLP and Text Preprocessing
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Tokenization, Lemmatization, Stop Words Removal
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Bag of Words and TF-IDF
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Word Embeddings – Word2Vec, GloVe
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Recurrent Neural Networks (RNNs) for NLP
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Sentiment Analysis
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Building Chatbots and Other NLP Applications
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