Machine Learning
Machine Learning
Start date
May 2023
Duration
10 Weeks
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What is this course about?
This course is professionally designed by professionals for individuals who want to break into cutting-edge Artificial Intelligence (AI) and take advantage of AI and its related technologies while building new applications from scratch or thinking of enabling the legacy applications to leverage the power of AI. This course starts from the basics of Artificial Intelligence and takes you step by step into the more advanced topics with hands on exercises, real-world examples, and problem solving with respect to industrial usage and best practices.
What is this course about?
This course is professionally designed by professionals for individuals who want to break into cutting-edge Artificial Intelligence (AI) and take advantage of AI and its related technologies while building new applications from scratch or thinking of enabling the legacy applications to leverage the power of AI. This course starts from the basics of Artificial Intelligence and takes you step by step into the more advanced topics with hands on exercises, real-world examples, and problem solving with respect to industrial usage and best practices.
Learning Outcomes:
Upon completion of this course, participants will be able to:
- Understand the fundamental concepts of Artificial Intelligence (AI), Neural Networks, Deep Learning, Natural Language Processing etc.
- Build, train, and deploy different types of predictive models with respect to industry best practices and large-scale real- world application requirements.
- Application of Deep Learning to real-world scenarios such as object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.
- Master Deep Learning at scale with accelerated hardware and GPUs.
- Use of popular Deep Learning libraries such as Keras, PyTorch, and Tensorflow applied to industry problems.
- Integrate the AI based predictive models into professional applications for real time predictions.
Learning Outcomes:
Upon completion of this course, participants will be able to:
- Understand the fundamental concepts of Artificial Intelligence (AI), Neural Networks, Deep Learning, Natural Language Processing etc.
- Build, train, and deploy different types of predictive models with respect to industry best practices and large-scale real- world application requirements.
- Application of Deep Learning to real-world scenarios such as object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.
- Master Deep Learning at scale with accelerated hardware and GPUs.
- Use of popular Deep Learning libraries such as Keras, PyTorch, and Tensorflow applied to industry problems.
- Integrate the AI based predictive models into professional applications for real time predictions.
Become an Artificial Intelligence
Expert in just 10 weeks
Become an Artificial Intelligence
Expert in just 10 weeks
Course Curriculum
Here is what's included in this Artificial Intelligence Course
- Introduction to Artificial Intelligence
- Fundamentals of Artificial Intelligence
- Applications of Artificial Intelligence
- Future of Artificial Intelligence
- Neural Network Introduction (Intuition behind Artificial Intelligence)
- Practical examples (Introduction to Numpy, Pandas and sci- kitlearn)
- Building block for Neural Networks
- Single NN
- Input/output Mapping
- Type Activation Functions
- Neural Network Architecture
- Practical examples (Introduction to ANN APIs and libraries)
- EDA / Data wrangling
- Back Propagation
- Loss Functions
- Hyperparameter Optimization
- Gradient
- Convolutional Neural Network
- Computer Vision real life application
- Overfitting/Underfitting
- NN issues (vanishing gradients etc)
- Model improvement and generalization techniques (Data Augmentation, Dropout, batch Normalization etc.)
- Recurrent Neural Network
- RNN variants (LSTMs etc)
- BI basic idea and importance
- BI tools and techniques (Power BI hands on)
- Introduction to Flask APIs
- Practical Project
- BI tools and techniques (Power BI hands on)
- Introduction to Flask APIs
- Practical Project
- Natural Language Processing and its essential libraries e.g. NLTK
- Tokenizing Text, Filtering Stop words, stemming and lemmatization
- Basic of Part of Speech, Word Embedding
- PCA
- Project Mid quires and discussion
- Time series prediction
- Feature Engineering
- Feature Extraction
- Feature Importance
- Big Data introduction and basic
- Offline/Online warehouse
- OLAP/OLTP
- Project final evaluation and discussion
Course Curriculum
Here is what's included in this Artificial Intelligence Course
- Introduction to Artificial Intelligence
- Fundamentals of Artificial Intelligence
- Applications of Artificial Intelligence
- Future of Artificial Intelligence
- Neural Network Introduction (Intuition behind Artificial Intelligence)
- Practical examples (Introduction to Numpy, Pandas and sci- kitlearn)
- Building block for Neural Networks
- Single NN
- Input/output Mapping
- Type Activation Functions
- Neural Network Architecture
- Practical examples (Introduction to ANN APIs and libraries)
- EDA / Data wrangling
- Back Propagation
- Loss Functions
- Hyperparameter Optimization
- Gradient
- Convolutional Neural Network
- Computer Vision real life application
- Overfitting/Underfitting
- NN issues (vanishing gradients etc)
- Model improvement and generalization techniques (Data Augmentation, Dropout, batch Normalization etc.)
- Recurrent Neural Network
- RNN variants (LSTMs etc)
- BI basic idea and importance
- BI tools and techniques (Power BI hands on)
- Introduction to Flask APIs
- Practical Project
- BI tools and techniques (Power BI hands on)
- Introduction to Flask APIs
- Practical Project
- Natural Language Processing and its essential libraries e.g. NLTK
- Tokenizing Text, Filtering Stop words, stemming and lemmatization
- Basic of Part of Speech, Word Embedding
- PCA
- Project Mid quires and discussion
- Time series prediction
- Feature Engineering
- Feature Extraction
- Feature Importance
- Big Data introduction and basic
- Offline/Online warehouse
- OLAP/OLTP
- Project final evaluation and discussion
Entry Requirements
There are no formal requirements for this certification.
Meet Our Trainers
Our experienced Artificial Intelligence expert are here to help you for your successful career
Adnan Zaidi
Chief AI Officer (CAIO) at PROXIMA.PK
MSc Network & Securities SZABIST
Programming languages and tools
Benefits of the course
Conduct specialized research to advance current technologies
Execute Industry-specific data mining and data analysis to create more value
Understand Software design and information architecture
