Global Certificate in ML for Journalism: Data-Driven
-- viewing nowThe Global Certificate in ML for Journalism: Data-Driven course is a comprehensive program designed to empower journalists with machine learning (ML) skills to thrive in the modern data-driven era. This course highlights the growing importance of ML in journalism, addressing industry demand for data-driven storytelling and analytical skills.
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Course Details
• Machine Learning Fundamentals: Introduction to ML, Types of ML, Supervised and Unsupervised Learning, Regression, Classification, Clustering
• Data Preprocessing: Data Cleaning, Data Wrangling, Data Normalization, Dimensionality Reduction, Feature Selection
• Python Programming: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn
• Natural Language Processing: Text Preprocessing, Tokenization, Stop Words Removal, Stemming, Lemmatization, Named Entity Recognition
• Data Journalism: Data Visualization, Interactive Storytelling, Data Ethics, Data Security
• Machine Learning Applications in Journalism: Predictive Analytics, Sentiment Analysis, Fact Checking, Automated Content Generation
• Evaluation Metrics: Accuracy, Precision, Recall, F1 Score, ROC Curve, AUC, Cross-Validation
• Machine Learning Project Management: Data Collection, Data Storage, Model Selection, Model Training, Model Evaluation, Model Deployment
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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