Top Certifications to Learn SAS, R, Python, Machine Learning and Big Data in 2026

ByJordan Brown

Data science and analytics are among the fastest-growing and highest-paying jobs in the world today. According to the World Economic Forum, data and AI will be one of the top emerging professions by 2025, with 97 million new job openings. LinkedIn‘s Emerging Jobs Report has consistently ranked data scientist, machine learning engineer, and big data engineer among the top 10 jobs with the highest growth rate and salaries.

To capitalize on this incredible opportunity, professionals need to continuously upskill and reskill themselves with the latest tools and techniques. One of the best ways to validate your knowledge and stand out to employers is by earning certifications from reputable organizations. In this article, we‘ll explore the top certifications to learn SAS, R, Python, machine learning and big data in 2024.

Why Certifications Matter

Certifications are not a substitute for hands-on experience and real-world projects, but they offer several benefits:

  • They provide a structured learning path and curriculum to master a skill or tool
  • They validate your knowledge and skills through rigorous exams and assessments
  • They showcase your dedication and commitment to continuous learning and improvement
  • They help you stand out in a competitive job market and increase your earning potential
  • They give you access to a community of certified professionals and exclusive resources

According to Global Knowledge‘s IT Skills and Salary Report, certified professionals earn 16% more on average than their non-certified peers. The report also lists several data science and big data certifications among the top-paying ones, such as:

  • Google Cloud Professional Data Engineer ($171,749)
  • CLOUDERA Certified Professional: CCP Data Engineer ($165,025)
  • AWS Certified Big Data – Specialty ($160,369)
  • SAS Certified Advanced Analytics Professional Using SAS 9 ($139,691)

SAS Certifications

SAS (Statistical Analysis System) is one of the oldest and most widely used tools for data analysis and statistical modeling, especially in industries like banking, healthcare, and pharmaceutical. SAS offers a wide range of certifications for different skill levels and job roles, from SAS Certified Specialist to SAS Certified Professional.

Here are some of the top SAS certifications focused on advanced analytics and machine learning in 2024:

1. SAS Certified Specialist: Machine Learning Using SAS Viya

  • Focus Area: Machine learning using SAS Viya
  • Prerequisites: 6+ months of experience with SAS or completion of SAS Programming 1 and Statistics 1 courses
  • Exam Format: 50-60 multiple-choice questions in 110 minutes
  • Key Topics: Data preparation, feature engineering, supervised and unsupervised learning, model assessment, deployment and monitoring
  • Price: $180 (includes free practice exam)
  • Validity: Lifetime

2. SAS Certified Professional: AI & Machine Learning

  • Focus Area: Designing and implementing AI and ML solutions using SAS Viya
  • Prerequisites: SAS Certified Specialist: Machine Learning Using SAS Viya or equivalent knowledge
  • Exam Format: 50-60 multiple-choice questions in 110 minutes
  • Key Topics: Deep learning, natural language processing, computer vision, forecasting, optimization, and model deployment and governance
  • Price: $250 (includes free practice exam)
  • Validity: 3 years

3. SAS Certified Advanced Analytics Professional Using SAS 9

  • Focus Area: Advanced analytics and predictive modeling using SAS 9
  • Prerequisites: 1+ year of experience with SAS or completion of 2-3 SAS courses
  • Exam Format: 60-75 multiple-choice questions in 150 minutes
  • Key Topics: Statistical analysis, data mining, machine learning, text analytics, optimization, and time series forecasting
  • Price: $250 (includes free practice exam)
  • Validity: 3 years

R Certifications

R is a popular open-source programming language for statistical computing and data analysis, with a vast ecosystem of packages for machine learning, data visualization, and more. While there are no official certifications from the R Foundation, several online learning platforms and universities offer comprehensive programs to master R for data science.

Here are some of the best R certifications and programs in 2024:

1. HarvardX‘s Data Science Professional Certificate

  • Platform: edX
  • Curriculum: 9 courses + 1 capstone project
  • Duration: 1-2 years at 2-3 hours/week
  • Key Topics: Data wrangling, statistical inference, machine learning, data visualization, and communication
  • Hands-on Projects: Several real-world case studies and a capstone project to build a portfolio
  • Price: Free to audit, $400 for verified certificate
  • Validity: Does not expire

2. Datacamp‘s Data Scientist with R Career Track

  • Platform: Datacamp
  • Curriculum: 22 courses + 15 projects
  • Duration: 88 hours
  • Key Topics: R programming, data manipulation, statistics, machine learning, and domain-specific applications (finance, healthcare, etc.)
  • Hands-on Projects: Guided and unguided projects using real-world datasets
  • Price: Requires Datacamp subscription ($25/month or $250/year)
  • Validity: Does not expire

3. Johns Hopkins University‘s Mastering Software Development in R Specialization

  • Platform: Coursera
  • Curriculum: 5 courses + 1 capstone project
  • Duration: 5 months at 5 hours/week
  • Key Topics: R programming, object-oriented programming, package development, and building data products
  • Hands-on Projects: Several assignments and quizzes + capstone project
  • Price: Free to audit, $50 per course for certificate
  • Validity: Does not expire

Python Certifications

Python has become the lingua franca of data science and machine learning, thanks to its simplicity, versatility and powerful libraries like NumPy, Pandas, Matplotlib, and Scikit-learn. Its ecosystem is constantly evolving with new tools and frameworks like TensorFlow, PyTorch, and Keras, making it essential for data scientists and engineers to keep up with the latest trends.

Here are some of the top Python certifications for data science and machine learning in 2024:

1. Google‘s Professional Machine Learning Engineer

  • Focus Area: Designing, building, and productionizing ML models using Google Cloud Platform
  • Prerequisites: 3+ years of industry experience in ML + proficiency in Python
  • Exam Format: 2-hour multiple-choice and hands-on exam
  • Key Topics: Data ingestion and preprocessing, model training and evaluation, deployment and monitoring, and MLOps best practices
  • Price: $200
  • Validity: 2 years

2. NVIDIA‘s Deep Learning Institute Certifications

  • Focus Area: Accelerated computing and deep learning using NVIDIA technologies
  • Certifications: NVIDIA DLI Certified Instructor, NVIDIA DLI Certified Developer, NVIDIA DLI Certified Data Scientist
  • Prerequisites: Basic knowledge of Python and deep learning + completion of relevant NVIDIA DLI courses/workshops
  • Key Topics: Neural networks, convolutional and recurrent nets, GANs, reinforcement learning, and GPU-accelerated libraries
  • Price: $200-$400
  • Validity: 2 years

3. Udacity‘s Data Scientist Nanodegree

  • Platform: Udacity
  • Curriculum: 4 courses + 5 projects
  • Duration: 4 months at 10 hours/week
  • Key Topics: Python programming, data wrangling, statistical analysis, machine learning, and data visualization
  • Hands-on Projects: Guided and open-ended projects using real-world datasets + capstone project
  • Price: $1400
  • Validity: Does not expire

Machine Learning and Big Data Certifications

Apart from tool-specific certifications, there are several vendor-neutral and multi-platform certifications that test your knowledge of machine learning algorithms and big data technologies. These are ideal for professionals who want to demonstrate their expertise in a domain and stay agnostic to specific tools.

Here are some of the top machine learning and big data certifications in 2024:

1. Stanford‘s Machine Learning Specialization (Coursera)

  • Focus Area: Foundational understanding of ML algorithms and techniques
  • Curriculum: 3 courses + 1 capstone project
  • Duration: 3 months at 5 hours/week
  • Key Topics: Supervised and unsupervised learning, deep learning, anomaly detection, recommender systems, and ML case studies
  • Capstone Project: Build a real-world ML system
  • Price: Free to audit, $50 per course for certificate
  • Validity: Does not expire

2. Cloudera Certified Associate (CCA) Data Analyst

  • Focus Area: Data analysis and exploration using SQL and Python on Cloudera‘s platform
  • Exam Format: 8-12 performance-based tasks in 120 minutes (remotely proctored)
  • Key Topics: Importing and exporting data, data wrangling, statistical analysis, and data visualization
  • Prerequisites: Basic knowledge of Python and SQL + Cloudera‘s Data Analyst Training course or equivalent experience
  • Price: $295
  • Validity: 2 years

3. Microsoft Certified: Azure Data Scientist Associate

  • Focus Area: Applying data science and ML techniques using Microsoft Azure
  • Prerequisites: Knowledge of Python or R + 1-2 years of experience with Azure
  • Exam Format: 40-60 questions in 180 minutes (remotely proctored)
  • Key Topics: Data exploration and preparation, experimentation and model training, model deployment and monitoring, and Azure ML pipelines
  • Price: $165
  • Validity: 1 year

The Future of Data Science and Analytics

Data science and analytics are evolving at a breakneck pace with the rise of cloud computing, automated machine learning, edge AI, and quantum computing. As data becomes more complex and ubiquitous, organizations will need professionals who can not only build ML models but also deploy and maintain them at scale, ensure their reliability and fairness, and communicate their impact to business stakeholders.

Some of the emerging trends and skills to watch out for in 2024 and beyond are:

  • MLOps and DataOps: Automating and streamlining the ML lifecycle from data preparation to model deployment and monitoring
  • Explainable AI (XAI): Making ML models more interpretable and transparent to build trust and meet regulatory requirements
  • Ethical AI: Ensuring that AI systems are fair, unbiased, and aligned with human values
  • Natural Language Processing (NLP): Building chatbots, virtual assistants, and sentiment analysis tools using advanced language models like GPT-3
  • Computer Vision: Developing intelligent video analytics, autonomous systems, and AR/VR applications using deep learning
  • Time Series Analysis: Forecasting demand, detecting anomalies, and optimizing supply chains using statistical and ML techniques
  • Graph Neural Networks (GNNs): Analyzing complex network data like social networks, recommendation engines, and biological pathways

To stay ahead of the curve, data science and analytics professionals should:

  1. Keep learning and experimenting with the latest tools and techniques through certifications, MOOCs, research papers, and side projects
  2. Develop a T-shaped skill set with deep expertise in a specific domain (e.g. NLP) and broad knowledge of other areas (e.g. cloud computing)
  3. Cultivate soft skills like communication, storytelling, and business acumen to effectively collaborate with stakeholders and drive impact
  4. Join online communities and attend conferences to network with peers and learn from industry leaders
  5. Contribute to open-source projects and Kaggle competitions to build a strong portfolio and showcase your skills

Conclusion

Data science and analytics offer a wide range of exciting career paths and opportunities for growth and impact. Certifications are a great way to accelerate your learning journey, validate your skills, and advance your career. However, they are not a silver bullet and need to be complemented with hands-on experience, real-world projects, and continuous learning.

We hope this comprehensive guide has given you a good overview of the top certifications to learn SAS, R, Python, machine learning, and big data in 2024. Remember to choose the ones that align with your career goals, learning style, and budget. Don‘t hesitate to start with free resources and MOOCs to explore your interests before investing in a certification.

Most importantly, have fun and enjoy the journey! Data science is a fascinating field with endless opportunities to learn, grow, and make a difference. As the famous statistician John Tukey said, "The best thing about being a statistician is that you get to play in everyone‘s backyard." So go out there, explore new domains, and use data to solve real-world problems and create value for society.

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