Advanced Data Science with IBM Specialization
Proficient in the fields of artificial intelligence, machine learning, and data science. Become an IBM-approved Expert in Artificial Intelligence, Machine Learning, and Data Science.
Description for Advanced Data Science with IBM Specialization
Level: Advanced
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On IBM provided by IBM
Duration: 2 months at 10 hours a week
Schedule: Flexible
Pricing for Advanced Data Science with IBM Specialization
Use Cases for Advanced Data Science with IBM Specialization
FAQs for Advanced Data Science with IBM Specialization
Reviews for Advanced Data Science with IBM Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Advanced Data Science with IBM Specialization
NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.
Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Learn to use generative AI tools to improve data science workflows, enhance datasets, and refine machine learning models through practical projects.
Use AI skills to advance your engineering career. Acquire practical knowledge regarding deep learning methodologies for computer vision.
Gain a comprehensive understanding of AI's potential, ethical considerations, and applications in efficient programming and common coding tasks using various LLMs.
Master Python programming for software development and data science, including core logic, Jupyter Notebooks, libraries like NumPy and Pandas, and web data gathering with Beautiful Soup and APIs.
Understand AI, its applications, concepts, ethical concerns, and receive expert career guidance.
The Deep Learning Specialization offers a comprehensive foundation in deep learning, practical skills in constructing neural networks, and prepares individuals to integrate machine learning into professional endeavors, advancing careers in AI.
The course's topics including the distinction between deep learning, machine learning, and artificial intelligence, the process of developing machine learning models, the difference between supervised and unsupervised learning, and the use of metrics for evaluating classification models.
Featured Tools
Construct and train neural networks and tree ensemble methods using TensorFlow, while applying effective machine learning practices for real-world data generalization.
Introduces the fundamental procedures for the development, scripting, and training of a machine-learned model in Google Cloud.
This course teaches aspiring data scientists to train and compare classification models using supervised machine learning techniques, focusing on practical applications and best practices.
Learn the basics of Generative AI and its economic and business impact, employment consequences, potential risks, and insights from industry leaders like Google and OpenAI.
Learn the Rasa framework to create AI-powered chatbots, which is suitable for Python programmers who are new to chatbot development and lack prior machine learning experience. This course covers the fundamental components and practical applications.