#selflearningplatform

NLP Engineer Essentials

Dive into the fundamentals of Python, Machine Learning, Deep Learning, and Natural Language Processing (NLP) in this essential course for aspiring NLP Engineers. Build a strong foundation for your journey into the world of AI and language processing.

Requirements

Basic Statistics Knowledge is beneficial

Basic English

Desktop or Laptop with minimum 8GB RAM and i5 processor

Reliable Internet Connection

Consistent Learner

Enthusiasm towards programming

What you’ll learn

Python fundamentals like variables, loops, functions, and essential coding concepts.

Machine learning techniques which are classification, regression, model training, and natural language data analysis.

Deep learning concepts which are neural networks, architectures, recurrent, convolutional networks.

Natural Language Processing intricacies like preprocessing, tokenization, vectorization, and text analysis techniques.

Hands-on projects real-world simulations, personalized feedback, and interactive learning.

Computer Vision Engineer Essentials

Computer Vision Engineer Essentials teaches Python basics, machine learning, deep learning, and computer vision. Students learn to code in Python, understand machine learning concepts, delve into deep learning techniques, and apply them to solve problems in computer vision.

Requirements

Basic Statistics for Data Science course completion is mandatory

Basic English

Laptop or Desktop with 8GB RAM and i5 processor

Reliable Internet Connection

Consistancy Learning

Enthusiasm towards programming

What you’ll learn

Python basics: Variables, loops, conditionals, functions, object oriented programming, coding exercises.

Machine learning: Supervised, unsupervised learning; building real world models.

Deep learning: Neural networks, activation functions, optimization, TensorFlow, PyTorch, complex tasks.

Computer vision: Image interpretation, object detection, classification, facial recognition, segmentation.

Practical learning: Hands-on projects, guided assignments, real-world applications, personalized feedback.

Artificial Intelligence Essentials

Artificial Intelligence Essentials covers Python basics for foundational programming, deep learning for understanding neural networks, computer vision for image recognition, and natural language processing for text understanding. Learn essential skills to explore AI applications across various domains.

Requirements

Completion of Machine Learning with Data Science course is mandatory

Basic English

Laptop or Desktop with minimum 8GB RAM and at least i5 processor

Reliable Internet Connecction

Consistancy in Learning

Enthusiam towards programming

What you’ll learn

Fundamental Python programming: Variables, loops, functions etc.

Basics of deep learning: Neural networks, TensorFlow, PyTorch.

Computer vision essentials: Image processing, object detection, classification.

Natural language processing (NLP) fundamentals: Sentiment analysis, named entity recognition.

Hands-on projects in AI: Practical application of learned concepts.

Data Scientist Essentials

Data Scientist Essentials teaches Python basics, machine learning, and deep learning. Learn Python programming from scratch, delve into machine learning algorithms for predictive analytics, and explore deep learning techniques for advanced data analysis. Gain essential skills for a career in data science.

Requirements

Completion of Basic Statistics for Data Science

Basic English

Laptop or Desktop with i5 processor

Reliable Internet Connection

Consistancy in Learning

Enthusiasm towards programming

What you’ll learn

Gain a solid understanding of Python programming fundamentals, including variables, loops, functions, and data structures.

Explore a wide range of machine learning algorithms, from supervised to unsupervised learning.

Dive into the cutting-edge field of deep learning, learning about neural network architectures like feedforward, convolutional, and recurrent networks.

Work on hands-on projects and real-world datasets across various domains, including finance, healthcare, e-commerce, and social media.

Develop practical skills in data manipulation, analysis, and visualization using libraries like NumPy, Pandas, and Scikit-learn.

Deep Learning Essentials

Unlock the world of AI and ML with our Deep Learning Essentials course. Gain essential knowledge and practical skills in deep learning concepts, neural networks, CNNs, RNNs, and LSTM networks. Master text classification, image recognition, and more for a rewarding career in Data Science.

Requirements

Basic Statistics for Data Science

Python Boot Camp for Data Science

Machine Learning & Data Science with Python

Basic English

Laptop with i5 processor

Reliable Internet Connection

What you’ll learn

Understand the fundamentals of deep learning and its significance in AI and data science.

Differentiate between machine learning and deep learning, and explore the reasons behind the popularity of deep learning.

Build a strong foundation in neural networks, including layers, nodes, and activation functions.

Learn how to train neural networks using forward and backward propagation techniques with practical Python examples.

Dive into convolutional neural networks (CNNs) for image analysis, mastering image classification.

Natural Language Processing Essentials

Explore Natural Language Processing (NLP) essentials in Python, covering sentence segmentation, word tokenization, stemming, and lemmatization. Dive into language models, including N-grams and word embeddings, and harness pre-trained models like BERT and GPT-3. Master text classification, sentiment analysis, Named Entity Recognition (NER), and AI-driven text generation.

Requirements

Python Boot Camp for Data Science course completion is very mandatory

Deep Learning Essentials course completion is very mandatory

Basic English

Laptop with i5 processor

Consistency in Learning

Reliable Internet Connection

What you’ll learn

Master the basics of Natural Language Processing and its vital components.

Build an NLP pipeline, including text preprocessing, with Python and popular libraries.

Understand language models, N-grams, and word embeddings like Word2Vec and GloVe.

Harness the power of pre-trained language models such as BERT and GPT3.

Perform text classification, sentiment analysis, and Named Entity Recognition.

Computer Vision Essentials

Master the fundamentals of Computer Vision with our course covering OpenCV and YOLO. Learn image processing, object detection, and facial recognition techniques. Gain practical skills to create real-world applications in autonomous vehicles and facial recognition systems.

Requirements

Python Boot Camp for Data Science course completion is very mandatory

Deep Learning Essentials course completion is very mandatory

Basic English

Laptop with i5 processor

Consistency in Learning

Reliable Internet Connection

What you’ll learn

Master the foundational principles of Computer Vision and its real-world applications.

Develop hands-on expertise in image processing using Python and the OpenCV library.

Gain a deep understanding of Object Detection techniques

Learn the art of Facial Recognition, from face detection using YOLO

Apply image enhancement, restoration, and segmentation methods to solve practical challenges.

"Deep Learning with Python Basics" teaches foundational concepts in using Python for deep learning. Students learn how to build neural networks, understand key algorithms, and apply them to solve problems like image recognition or natural language processing.

Requirements

Enrolling Basic Statistics for Data Science is mandatory

Completion of Machine Learning with Data Science is mandatory

Basic English

Laptop with i5 processor

Reliable Internet Connection

Consistancy in Learning

What you’ll learn

Python programming from scratch with various working examples and exercises. Comprehensive coding skills.

Understand the fundamentals of deep learning and its significance in AI and data science.

Differentiate between machine learning and deep learning, and explore the reasons behind the popularity of deep learning.

Build a strong foundation in neural networks, including layers, nodes, and activation functions.

Learn how to train neural networks using forward and backward propagation techniques with practical Python examples.