When Are the Next Udemy Data Courses Coming?

TL;DR

A Python with DSA bootcamp was planned for release by September 28, 2024, with more than 55 hours of material covering Python basics, data structures, LeetCode problems, projects, and interview questions. A separate MLOps course was also being designed around an end-to-end real-world project, open-source tools, cloud deployment, CI/CD, monitoring, and data pipelines.

Transcript

hello all my name is kushak and welcome to my YouTube channel so guys I hope you have explored my udmi courses and you're also exploring my YouTube videos uh where I have been uploading a lot of contents specifically in YouTube now I have changed into a longer form videos where each and every video of mine is somewhere around 30 to 45 minutes and b... Read More

Key Insights

• The recommended starting point is the mathematics course for learners beginning with data science fundamentals, after which they can choose either the data analyst path or the machine learning, NLP, MLOps, and deployment path before studying generative AI.
• The Python with DSA bootcamp was already being recorded and was planned for release by September 28, 2024. Its structure begins with Python basics, continues into data structures and algorithms, and adds projects, LeetCode exercises, and interview-oriented preparation.
• The Python with DSA course was expected to contain more than 55 hours of material. The instructor also planned continuing updates that would add further interview questions, including questions connected with preparation for FAANG and other product-based companies.
• The planned Python course includes a second mentor in addition to Krish, although the collaborator's name was not announced. The prospective mentor was described as experienced in cracking product-based companies, highly rated on LeetCode, and familiar with solving many LeetCode problems.
• The dedicated MLOps course is intended for machine learning engineers and data scientists who want instruction from basic to advanced levels. It responds to requests for clearer examples of individual MLOps tools, with a particular emphasis on tools that are open source.
• The draft MLOps curriculum covers ingestion with Kafka and Airflow, database integration, pipeline orchestration, feature storage, data validation, and exploration with Apache Spark and pandas. It also includes notebooks, scikit-learn, MLflow, DVC, DAGsHub, and the MLflow model registry.
• The deployment portion of the MLOps curriculum includes Docker, Kubernetes, GitHub Actions, image creation, and publication to a private repository or Docker Hub. The instructor was considering both AWS and Azure, while Google Cloud content could be added later if sufficient demand emerged.
• The MLOps course centers on an end-to-end real-world problem so learners can understand how tools fit into an actual project and potentially reference the work on their resumes. Monitoring and pipeline automation were planned with Prometheus, GitHub Actions, and CircleCI.

Questions & Answers

Q: What is the recommended order for taking these data courses?

Learners starting from the basics are advised to begin with Mathematics: Basics to Advanced for Data Science and GenAI. They can then choose either the Complete Data Analyst Bootcamp or the Complete Machine Learning, NLP Bootcamp, MLOps and Deployment course. After completing one of those paths, they can continue with the generative AI course using LangChain. Learners focused specifically on Gemini Pro can instead explore the hands-on Gemini application course.

Q: When was the Python with DSA bootcamp expected to launch?

The Python with DSA bootcamp was expected to become available by September 28, 2024. Recording had already started when the update was given. The planned course begins with Python fundamentals, moves into data structures and algorithms, and includes multiple projects, extensive LeetCode problem solving, and continuing additions of interview questions aimed at preparation for product-based companies and FAANG-related interviews.

Q: What topics will the Python with DSA course cover?

The planned curriculum starts with basic Python and then advances into data structures and algorithms. It also includes multiple projects and extensive practice with LeetCode questions, reflecting feedback gathered from college freshers. The course was designed as a complete bootcamp rather than a short introduction, and further interview questions were expected to be added through later updates.

Q: How long will the Python with DSA bootcamp be?

The Python with DSA bootcamp was planned to include more than 55 hours of content. That duration was intended to support a large number of coding problems, instruction beginning with Python basics, coverage of data structures and algorithms, and multiple projects. The course was also expected to receive additional interview questions over time instead of remaining fixed after its initial release.

Q: What will the dedicated MLOps course teach?

The MLOps course is planned as a basic-to-advanced program for machine learning engineers and data scientists. Its draft syllabus covers MLOps components, data ingestion, databases, orchestration, feature storage, validation, exploration, version control, experimentation, model development, registries, containers, Kubernetes, CI/CD, cloud deployment, monitoring, and triggers that automatically start a machine learning pipeline.

Q: Which tools are included in the planned MLOps curriculum?

The draft curriculum names Kafka, Apache Airflow, Apache Spark, pandas, Jupyter notebooks, scikit-learn, MLflow, DVC, DAGsHub, Docker, Kubernetes, GitHub Actions, CircleCI, and Prometheus. It also discusses database integration, private image repositories, Docker Hub, and cloud deployment. AWS and Azure were under consideration, while Google Cloud content could be created later if learners requested it.

Q: How will the MLOps course use a real-world project?

The course is planned around an end-to-end real-world problem that demonstrates how each MLOps tool fits into the machine learning project lifecycle. The instructor intends to show implementation in a realistic scenario rather than presenting tools only in isolation. The resulting project is also meant to be suitable for learners to mention or demonstrate on their resumes.

Q: What Udemy discount was available for the existing courses?

The existing Udemy courses were offered for ₹399 through coupon links in the description, with the stated coupon valid for one day and the next coupon expected after 10 days. The offer covered lifetime access to listed courses in mathematics, data analysis, machine learning and NLP, generative AI with LangChain and Hugging Face, Gemini Pro applications, and Figma.

Summary & Key Takeaways

• The recommended learning sequence begins with mathematics for data science, followed by either the data analyst bootcamp or the machine learning, NLP, MLOps, and deployment bootcamp. Students can then progress to the generative AI course using LangChain, while those focused specifically on Gemini Pro can choose the project-oriented Gemini application course.

• The planned Python with DSA bootcamp starts with Python fundamentals, advances into data structures and algorithms, and includes projects plus extensive LeetCode problem solving. The instructor planned to collaborate with another mentor experienced in product-based company preparation and intended to keep adding interview questions associated with FAANG-focused preparation.

• The proposed MLOps course covers the machine learning lifecycle through a real-world problem that students can reference on their resumes. Its draft curriculum includes ingestion, orchestration, validation, exploration, version control, experimentation, model registries, containers, Kubernetes, CI/CD, cloud deployment, monitoring, and automated pipeline triggers using predominantly open-source tools.