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Core IT Trainings

At Core IT Trainings, we offer expert IT training and visa support tailored to your needs.

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Courses / Artificial Intelligence / AI and Neural Networks: Building Intelligence with Python
Artificial Intelligence
5.00 /1

AI and Neural Networks: Building Intelligence with Python

Training

Real-time, Hands-on, & Practical

Certification

Course Completion Certificate

Support

Job Assistance & Career Guidance

Payment Plan

Interest Free Installment Option

About Course

Start your journey in artificial intelligence with our comprehensive AI and Neural Networks course! This course provides an in-depth understanding of AI, starting with Python essentials for data science and advancing into complex neural network architectures. Why should you learn this course? AI and deep learning skills are among the most in-demand across industries today. This program is designed to give you hands-on experience with neural networks, from the foundations of perceptrons and gradient descent to advanced topics like convolutional and recurrent neural networks.

With a focus on practical applications, you’ll explore essential AI techniques for image processing, text mining, and sequential data through projects and real-world examples. This course also covers various activation functions, loss functions, and training techniques like regularization, batch normalization, and dropouts to fine-tune model performance. By the end, you’ll be well-prepared to build, train, and optimize neural networks for complex tasks, gaining valuable skills for a career in AI and data science.

Whether you aim to innovate in tech, enhance your data skills, or start an AI-focused career, this course equips you with the knowledge and experience to succeed.

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What Will You Learn?

  • Fundamentals of Python for data science.
  • Understanding neural network structures and activation functions.
  • Implementing and training artificial and convolutional neural networks.
  • Conducting text mining and NLP tasks like tokenization, stemming, and Word2Vec.
  • Mastering recurrent neural networks for sequential data processing.

Course Curriculum

Introduction to Python for Data Science

  • Artificial Neural Networks
  • Limitations of Algorithmic Solutions
  • Networks in the Brain
  • Perceptrons
  • Loss Functions
  • Regularization Functions
  • Gradient Descent and Local Minima
  • Learning Rate
  • Multi-Layer Perceptron
  • Back-Propagation Algorithms
  • Vanishing Gradients and Overfitting
  • Activating Functions: Sigmoid, tanh, ReLU, Leaky ReLU, ELU
  • Auto-encoding
  • Weight Initializing
  • Batch Normalization
  • Dropouts

Neural Networks

  • Understanding Images
  • Traditional Approaches
  • 1D & 2D Convolutions
  • Hyper-parameters: Depth, Size, Stride, Padding
  • Pooling
  • CNN Architectures: LeNet-5, AlexNet, ZFNet, VGGNet, Inception, ResNet
  • Pre and Post Processing
  • Transfer Learning

Convolutional Neural Networks (CNN)

  • Word Representations
  • Tokenization, Stemming, and Lemmatization
  • TF-IDF
  • Word2Vec and Embeddings
  • Search and Ranking

Text Mining

  • Sequential Data and RNN Architecture
  • Back Propagation Through Time
  • Applications of LSTM and GRU

Recurrent Neural Networks (RNN)

Ratings & Reviews

5.0

Total 1 Rating

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Featured Review

MK

Manpreet Kaur

6 months ago

It covered all the essential concepts and algorithms needed for intermediate-level data science. The hands-on practice sessions really helped me grasp time-series forecasting and regression.

£1,650 £2,250
-27%
Course Snapshot:
Course Duration 3 Months
Course Timing Mon-Fri (2 hours/day)
Training Type Virtual/Online
Skill Level Intermediate
Certificate Yes
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Requirements

  • Basic programming knowledge (Python preferred).
  • A computer with Python and Jupyter Notebook installed.
  • Interest in machine learning, AI, and data science.

Audience

  • Aspiring data scientists and AI engineers.
  • IT professionals looking to expand into machine learning.
  • Data analysts interested in advancing to deep learning.
  • Students and researchers in computer science and AI.

Material Includes

  • 60+ hours of structured video content and practical labs.
  • Projects on image processing, NLP, and sequential data.
  • Detailed guides on loss functions, gradient descent, and activation functions.
  • Access to sample datasets and code examples.
  • Downloadable resources on neural network architectures and techniques.
At Core IT Trainings, we are passionate about empowering individuals to reach their full potential in the dynamic and ever-evolving field of IT.

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Westlink House, 981 Great West Road, Brentford, England, TW8 9DN