Close

Explore AI

Explore GPTs

Explore AI News

Explore AI Videos

Explore AI for Jobs

Latest Data Science Dojo AI Videos

Find the latest for Data Science Dojo company videos

Follow
... 12:12
Launching DSA + Gen AI with Projects | DSA in C++ and Java | Python for ML | 500+ DSA Questions

Fraz

1+ months ago 7K views

Engineers, particularly freshers, question the declining relevance of data structures and algorithms (DSA) in hiring practices. Insights from engineers and recruiters at Google, Microsoft, and Amazon reveal that DSA remains crucial for assessing problem-solving skills, ensuring candidates can be trained in any technology. A new course will cover comprehensive DSA while introducing generative AI and Python to enhance portfolios and knowledge of market trends. Students can also access free playlists on data structures and algorithms while the course, scheduled over 6-8 months, provides mentorship and focuses on interview preparation and career paths in AI and machine learning.
04:37 - 04:42

Career options in AI and ML will be explored during the course.

Machine Learning Education
... 5:55
The Top 5 AI Training In 2025 | Beginners AI Learners Roadmap | Here’s How to Start!

Tech Simplified

1+ months ago 1K views

Structured learning paths are crucial for gaining practical AI skills. Starting with foundational courses like TechSimplified's Microsoft AI 900 prepares learners for advanced topics in AI responsibly. DataCamp's hands-on approach enhances understanding and skill application through interactive exercises. Key courses include developing large language models with PyTorch, creating AI applications with LandChain, and using OpenAI's API for rapid deployment. A 90-day roadmap can effectively guide this learning journey, simplifying complex concepts and making AI accessible to everyone. Now is the best time to begin learning AI, especially with current discounts available.
02:48 - 03:15

LandChain empowers development of advanced, independent AI applications.

Machine Learning Education
... 9:14
Data Lakehouse, Data Quality and Scaling AI

The Ravit Show

1+ months ago 4K views

Data lake house advancements reflect significant industry progress over the past two years. Enterprises are increasingly focused on customizing AI models with their proprietary data, incorporating both structured and unstructured data to enhance operational productivity and market share. Data quality remains critical, emphasizing the importance of training models effectively with reliable data. Key misconceptions involve viewing structured and unstructured data as separate entities, rather than integrating them for improved accuracy in AI applications. As AI continues to evolve, the lake house architecture will be integral to capturing and utilizing diverse data sources.
02:44 - 03:40

Misconception exists in treating structured and unstructured data as separate; integration is key.

Big Data Analytics Research & Innovations
... 23:53
#646: AI in e-commerce with Oren Inditzky, Wix

The Agile Brand with Greg Kihlstrom®

1+ months ago 2K views

Data is a powerful asset for storytelling and decision-making in businesses, but transforming it into actionable insights poses challenges. Domo’s AI-driven platform enhances data handling, enabling teams to prepare, analyze, visualize, and automate their data usage. This platform empowers users to make swift decisions and foster growth efficiently. The potential of generative AI in e-commerce is highlighted, particularly in automating content creation and optimizing user interactions. Accessibility to AI tools democratizes the e-commerce landscape, ensuring that smaller businesses can compete effectively by leveraging technology that simplifies processes like website design and product management.
08:11 - 09:39

AI aids in dynamic pricing and inventory management, optimizing business performance.

Wix Machine Learning Retail
... 37:13
How my AI Agent Team Analyses 427,000 rows in Seconds with n8n (Claude 3.7 and ChatGPT 4.5)

Frank Nillard | AI Studio

1+ months ago 2K views

Data analysts often spend extensive time pulling and cleaning data from large databases to gain insights. The promotion of a new system allows this entire process to be automated, enabling quick access to insights using natural language. The system is designed with an orchestrator agent that connects to a SQL database, extracts data, and generates visualizations efficiently. It utilizes advanced models such as GPT 4.5 and Claude 3.7, leveraging their capabilities to improve the data analysis process and reduce reliance on traditional data analysis teams, ultimately driving better business decisions.
01:39 - 01:54

Introduces orchestrator agent, SQL agent, and visualization agent.

n8n Big Data Analytics Research & Innovations
... 9:33
Live AI CRASH COURSE-Most Extensive Series For Data Science, Generative And Agentic AI

Krish Naik

1+ months ago 10K views

Krishak announces a free live AI crash course on data science, generative AI, and agentic AI on his YouTube channel. The course aims to cover multiple topics and includes real-world applications and industrial use cases. Participants can expect live interactions and access to a dashboard with materials after sessions. Additionally, there's a focus on community engagement, inviting suggestions for future crash courses. Experts will also be brought in to enhance learning, aiming to stay updated with emerging trends in AI technology and implementation.
06:02 - 06:29

Introduction of community discussions to enhance peer learning and case studies.

Machine Learning Education
... 7:20
Data Scientist vs Data Analyst vs Data Engineer: Roles, Responsibilities, Salary, AI Impact !!

CareerRide

1+ months ago 1K views

Data is essential in today's business landscape, driving decision-making and innovation. Companies globally leverage data to enhance performance, reduce costs, and improve customer experiences. As data roles gain prominence, there is a significant demand for data professionals, including data analysts, data engineers, and data scientists, each with distinct skills and responsibilities. Data analysts focus on visualizing and reporting data, while data engineers build data pipelines, and data scientists apply advanced techniques in AI and machine learning to predict outcomes. The future of data roles will incorporate AI technologies, enhancing strategic tasks and decision-making.
Big Data Analytics Education
... 51:1
Data Engineering for Artificial Intelligence | The Hidden Power

Education Nest

1+ months ago 2K views

Data engineering is a crucial component of modern AI and analytics. It serves as the backbone for AI-driven solutions, enabling organizations to process and transform raw data into actionable insights. Key topics include the role of data engineers in building pipelines, ensuring data security, and leveraging technologies like Apache Kafka, Spark, and Python for effective data management. The session emphasizes the demand for skilled data engineers in today's data-driven landscape, highlighting the importance of data engineering in supporting machine learning models and decision-making processes within businesses across various industries.
29:23 - 29:55

Utilizing data pipelines streamlines data ingestion and processing for AI.

Big Data Analytics Education
... 51:1
Data Engineering for Artificial Intelligence | The Hidden Power

Education Nest

1+ months ago 2K views

Data engineering is a crucial component of modern AI and analytics. It serves as the backbone for AI-driven solutions, enabling organizations to process and transform raw data into actionable insights. Key topics include the role of data engineers in building pipelines, ensuring data security, and leveraging technologies like Apache Kafka, Spark, and Python for effective data management. The session emphasizes the demand for skilled data engineers in today's data-driven landscape, highlighting the importance of data engineering in supporting machine learning models and decision-making processes within businesses across various industries.
29:23 - 29:55

Utilizing data pipelines streamlines data ingestion and processing for AI.

Big Data Analytics Education