Soil Science Courses

NES Middle Grades Social Science (202) Prep

Comprehensive preparation for NES Middle Grades Social Science exam, covering history, geography, political science, and economics through engaging lessons and quizzes.

• Study.com
• Self-Paced
• Paid Course

Praxis General Science (5436) Prep

Comprehensive preparation for the Praxis General Science exam, covering key topics in physics, chemistry, biology, geology, and astronomy. Reinforces essential knowledge for test success.

• Study.com
• 1 day 12 hours 48 minutes
• Self-Paced
• Paid Course

General Social Science Lessons

Explore diverse social science disciplines, from cultural studies to sociology, gaining insights into human behavior, language, education, and societal structures.

• Study.com
• 2 days 9 hours 44 minutes
• Self-Paced
• Paid Course

General Computer Science Lessons

Comprehensive overview of computer science, information technology, and general technology concepts, with practical exercises and a final test.

• Study.com
• 8 hours 24 minutes
• Self-Paced
• Paid Course

EDUCBA

Statistics for Data Science with Python

Master statistical analysis and predictive modeling using Python, Pandas, and NumPy through hands-on exercises covering descriptive stats, hypothesis testing, and regression techniques.

• Coursera
• 8 hours 3 minutes
• Self-Paced
• Paid Course

Computer Science 104: Intro to Web Development

Discover HTML, CSS, and JavaScript fundamentals to build interactive websites and launch your web development journey with hands-on projects and real-world applications.

• Study.com
• 18 hours 16 minutes
• Self-Paced
• Paid Course

Advanced Python: Data Science, Testing, and Distribution

Master data science fundamentals, exception handling, unit testing, and package distribution to complete your advanced Python programming journey.

• Coursera
• 7 hours 55 minutes
• Self-Paced
• Paid Course

Python Data Science: Environment Setup

Discover how to set up a Python data science environment using Anaconda and Jupyter for effective business data analysis and knowledge extraction.

• Coursera
• 2 hours 25 minutes
• Self-Paced
• Paid Course

Python Data Science: NumPy

Master NumPy fundamentals for data science: create arrays, load/save data, analyze datasets, and transform arrays for effective data manipulation and insights extraction.

• Coursera
• 4 hours 25 minutes
• Self-Paced
• Paid Course

Python Data Science: pandas, Matplotlib, and Seaborn

Master pandas DataFrames, Matplotlib, and Seaborn to analyze, manipulate, and visualize data effectively in Python for comprehensive data science workflows.

• Coursera
• 10 hours 20 minutes
• Self-Paced
• Paid Course

Edureka Career Certificate

No-Code Data Science and Machine Learning

Master data science and ML through no-code tools like KNIME, Orange, and Google Vertex AI. Build pipelines, train models, and deploy solutions without programming.

• Coursera
• 8 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 2 courses

Career Certificate

Using Data Science Tools in Python

Master Python's essential data science libraries to extract insights from data and drive business decisions through hands-on analysis, visualization, and programming techniques.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Career Certificate

R Programming for Data Science

Master R programming fundamentals for data analysis, statistical modeling, and visualization to extract valuable insights and create predictive models in 4 weeks.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Packt Career Certificate

Google Colab for Data Science & AI using Python

Master Python programming and Google Colab for data science and AI through hands-on exercises, covering essential libraries like NumPy, Pandas, and Matplotlib for real-world projects.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course

Packt

Foundations of ML & Python for Data Science

Gain insights into machine learning fundamentals and Python programming for data science, covering statistical techniques, key libraries like NumPy and Pandas, and practical applications across industries.

• Coursera
• 14 hours 15 minutes
• Self-Paced
• Paid Course