Talha Fareedi Machine Learning, Generative AI, Data Science
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**Teaching Profile: Machine Learning and Data Science**

With over 4 years of hands-on experience in the field of Machine Learning and Data Science, I bring a wealth of practical knowledge and expertise to my teaching endeavors. Holding certificates in Machine Learning from IBM, Python for Data Science, and Supervised Learning from prestigious institutions such as Stanford Online and DeepLearning.AI, I am dedicated to imparting cutting-edge skills to aspiring data scientists and machine learning enthusiasts.

My specialization in Supervised Learning from DeepLearning.AI has equipped me with advanced techniques and methodologies crucial for understanding and implementing predictive modeling effectively. Furthermore, my proficiency in Deep Learning with TensorFlow enables me to delve into complex neural network architectures and their applications across various domains.

One of my key areas of focus is natural language processing (NLP) and conversational AI. I have been actively involved in creating chatbots and leveraging advanced NLP models such as Longformer from Langchain and Hugging Face. Through practical projects and real-world examples, I aim to demystify these technologies and empower students to harness the full potential of AI-driven language processing.

In my teaching approach, I prioritize hands-on learning and practical implementation. By providing students with real datasets and guiding them through the process of building machine learning models from scratch, I ensure they develop a strong foundation and gain confidence in tackling diverse data science challenges.

With a passion for both teaching and learning, I am committed to staying updated with the latest advancements in the field and continuously refining my teaching methodologies to deliver a comprehensive and enriching learning experience. Whether you're a beginner looking to enter the world of data science or an experienced professional seeking to enhance your skills, my teaching profile offers a roadmap for success in the exciting and rapidly evolving field of machine learning and AI.

Subjects

Deep learning with Python programming Beginner-Expert
Backend Development (Django) Beginner-Expert
Machine Learning Model deployment using flask and streamlit Beginner-Expert
LangChain Beginner-Expert
Generative AI Beginner-Expert

Experience

Data Analyst (Sep, 2022–Dec, 2023) at Insignia Financial
AI Engineer (Apr, 2022–Feb, 2023) at Proxima AI
Teacher (Jul, 2020–Present) at Home Tutiions

Home tutions during my education in islamia university of bahawakpur

Education

Machine Learning Specilization (Mar, 2023–Feb, 2024) from Deep Learning.ai
Deep Learning With Tensorflow (May, 2022–Jun, 2022) from IBM Cognitive class
FULL Stack Python (Jun, 2021–May, 2022) from PNY Trainings
Bachelor's in Computer science (May, 2019–Mar, 2023) from The islamia university of Bahawalpur, pakistan–scored 3.8

Fee details

Rs15,000–25,000/month (US$53.82–89.69/month)

it depends on student prior knowneldge and engament in the activity

Courses offered

Full Stack Artifical Intelligence
- US$50000
- Duration: 2 Months
- Delivery mode: Flexible as per the student
- Group size: Individual
- Instruction language: Urdu, English
- Certificate provided: Yes
Embark on a transformative journey into the realm of Artificial Intelligence with our comprehensive Full Stack AI course. Designed for aspiring AI engineers, data scientists, and tech enthusiasts, this course offers a holistic approach to mastering the fundamental concepts, tools, and techniques essential for building intelligent systems from end to end.

Curriculum Highlights:

Foundations of AI: Dive into the core principles of artificial intelligence, including machine learning, deep learning, and neural networks. Gain a solid understanding of algorithms, data structures, and mathematical foundations crucial for AI development.

Data Science Essentials: Explore the intricacies of data manipulation, analysis, and visualization using Python and popular libraries such as NumPy, Pandas, and Matplotlib. Learn how to extract insights from raw data and prepare it for AI modeling.

Machine Learning Mastery: Delve into supervised, unsupervised, and reinforcement learning techniques. Understand how to build predictive models, classify data, and perform clustering tasks using industry-standard algorithms.

Deep Learning Fundamentals: Unlock the power of deep neural networks for image recognition, natural language processing, and more. Learn how to design, train, and deploy deep learning models using frameworks like TensorFlow and PyTorch.

Full Stack Development: Seamlessly integrate AI models into real-world applications by mastering full stack development principles. Explore frontend technologies such as HTML, CSS, and JavaScript, and backend frameworks like Flask or Django for building robust, scalable AI-driven web applications.

Natural Language Processing (NLP): Harness the potential of NLP for sentiment analysis, text generation, and language translation. Explore state-of-the-art NLP models and libraries such as NLTK, SpaCy, and Hugging Face Transformers.

Computer Vision: Gain hands-on experience in computer vision tasks such as object detection, image segmentation, and facial recognition. Learn how to leverage convolutional neural networks (CNNs) and pre-trained models for image processing.

Ethical and Responsible AI: Explore the ethical considerations and societal impacts of AI technologies. Understand the importance of fairness, transparency, and accountability in AI development and deployment.