You can fast-track your DASCA credentialing process if you're a student or alumnus of a DASCA-accredited/ recognized institution.
Read moreIn support of our mission to empower data analysts, scientists and engineers, we’ve introduced two platforms – Data Science Current and Data Engineering Digest – offering curated content tailored to your professional needs. These platforms provide expert insights, the latest industry trends, and personalized updates to help you stay informed and ahead in the data science field.
Sign up today to customize your experience and receive newsletters with cutting-edge content, expert interviews, and exclusive updates.
Exclusive blogs that discuss the latest innovations and breakthroughs in the world of Data Science. Stay ahead with expert insights that drive industry change.
Explore the latest trends, innovative practices, and cutting-edge technologies shaping Data Science today.
Engage with top industry experts as they discuss real-world applications, key challenges, and the future of Data Science. Gain deep insights to elevate your expertise.
Share your expertise with the global DASCA community. Contribute insights and establish yourself as a thought leader in Data Science.
Stay informed with the latest DASCA announcements, industry news, and upcoming events.
Explore DASCA’s comprehensive certification paths tailored for professionals in:
Validate your expertise in designing, building, and managing Big Data infrastructure.
ABDE™ Brochure SBDE™ BrochureMaster the tools and techniques for advanced data analysis and insight generation.
ABDA™ Brochure SBDA™ BrochureBecome an expert in data science methodologies and applications.
SDS™ Brochure PDS™ BrochureChoose your qualification and experience level to find the DASCA certification that aligns with your career goals.
Learn about the steps to earn your DASCA certification, from application to becoming a certified professional.
DASCA certification exams are available online worldwide, accessible in 180+ countries with 5th-generation TEI technology.
Find answers to common questions about DASCA certifications, exam process and policies.
Showcase your DASCA certification with digital badges recognized worldwide.
Discover how DASCA Accreditation enhances data science and AI education, ensuring global recognition and academic excellence.
Understand how DASCA Accreditation sets the benchmark for excellence in data science and AI education, aligning institutions with global industry standards.
Examine the framework that upholds high benchmarks for curriculum, faculty expertise, and industry relevance in data science and AI programs.
Understand the institutional and program-level requirements to assess your readiness for pursuing DASCA Accreditation.
Explore the step-by-step process to achieve DASCA Accreditation through a rigorous, globally benchmarked, and digitally powered evaluation.
Discover how DASCA Accreditation enhances institutional reputation, academic quality, and global competitiveness in data science and AI education.
Access comprehensive guides, support tools, and subsidy programs designed to assist institutions throughout their accreditation journey.
Learn about the global network of academic and industry experts who support institutions in delivering high-quality data science and AI education.
Get answers to common questions about institutional eligibility, the accreditation process, ongoing compliance and more.
Begin your DASCA accreditation journey and position your institution among global leaders in data science and AI education.
Join the rapidly growing DASCA network of leading tech schools, higher education institutions, IT training companies, and government organizations. Partner with DASCA to prepare your students and professionals for globally recognized data science certifications. Start your partnership journey today.
Know moreGet your academic programs DASCA accredited and join an elite group of institutions shaping the future of data science. Leverage the World Data Science & AI Initiative's subsidy program to strengthen your academic offerings.
Read More>Get your teams DASCA-certified and ensure they meet global standards in data science. Partner with us to drive sustainable skills development and long-term growth for your organization.
Read More>Offer training programs that prepare candidates for DASCA certification exams. Position your academy as a trusted provider of exam-focused education for aspiring data science professionals.
Read More>Collaborate with DASCA to promote standards-based data science education. Align your curriculum with DASCA’s globally recognized framework and contribute to advancing the field’s future.
Read More>The DASCA Body of Knowledge and the Essential Knowledge Framework (EKF™) define the most rigorous standards for professional excellence in Data Science. Together, they ensure that DASCA certifications reflect the highest levels of competency and expertise for data professionals.
Read moreThe DASCA Body of Knowledge serves as the foundation for all DASCA certifications, ensuring each credential reflects deep, industry-wide standards of excellence in data science and analytics.
The Essential Knowledge Framework (EKF™) outlines the authoritative skills and knowledge required for data science professionals, providing a clear, structured path to achieving DASCA certifications.
DASCA sets industry-leading standards, frameworks, certifications, and accreditation programs to develop skilled Big Data analysts, engineers, and data scientists.
Uncover DASCA’s dynamic Credentialing Framework, which reinforces industry leadership through its Essential Knowledge Framework (EKF™) and Data Science body of knowledge.
Learn about DASCA’s governance structure, ensuring neutrality, independence, and adherence to the highest credentialing standards.
Commit to integrity in data science. Discover the principles that guide DASCA-certified professionals in ethical, responsible, and transparent practices.
Explore how Big Data is transforming industries globally, driving innovation, and creating new opportunities across sectors.
Discover the emerging career tracks in Data Science and how professionals are adapting to the rapidly evolving data landscape.
DASCA’s pioneering credentials for data analysts, data engineers, and data scientists are cross-platform, vendor-neutral, and adaptable across a wide range of industries and operational levels. Our certifications equip professionals with the skills they need to excel in today’s dynamic data landscape, ensuring they are prepared for diverse roles in data-driven environments.
Explore how DASCA certifications prepare you for roles in diverse industries, providing cross-platform skills and vendor-neutral expertise.
Equip yourself with globally recognized credentials to start your career in data science on the right foot.
Get your institution DASCA-accredited to join the league of the leading global Data Science educators.
Discover how DASCA-certified professionals bring value to your organization with advanced data science skills.
Start your data science journey with DASCA. Whether you're an individual pursuing certification, an institution seeking DASCA accreditation, or an organization exploring partnership, the process is simple and entirely online to help you achieve your goals.
For any questions about certifications, partnerships, or DASCA accreditation, feel free to get in touch.
Stay up to date with DASCA’s latest announcements and developments. Explore press releases, certification updates, expert insights on data science trends, and learn about DASCA’s global initiatives.
"After supervised learning — Transfer Learning will be the next driver of ML commercial success."
- Andrew NG, one of the world’s foremost data scientists
Machine learning has evolved from the early days of mere datasets feeding into algorithms. And, with evolutions, come newer avatars in themselves. In the world of data science and more specifically, machine learning, deep learning has carved out its niche in the hearts of scientists and engineers in companies across the world and the technology has proven, beyond a doubt, to match or even surpass human level proficiency in analyzing and extracting features of a fixed dataset and even streaming data.
The question that’s probably on every data scientist’s mind today is “how do we make this human intensive training process simpler, faster and more accurate without having to return to the drawing board? Especially when there isn’t enough data to train a model?”
Enter The World of Transfer LearningTo begin with, transfer learning is just as it sounds - a baseline to facilitate richer feature extraction and top training algorithms piggybacking on already existing successful models to provide deeper and more refined results in feature extraction. By definition, transfer learning is a machine learning strategy wherein a machine learning model trained for one task is repurposed for another task.
Transfer learning requires a whole different approach compared to a traditional machine learning model, wherein data sets are fed into single models and the output is a trained ML model. In transfer learning, the model used by a source task (or source domain) is applied and then fine-tuned to achieve a destination task (or destination domain). The assumption, in this case, is that the source task and the destination task are adequately similar in nature. Transfer learning is especially useful in cases where the destination model or domain data is sparse.
Typical Transfer Learning ModelA Deep learning convolutional neural network automates feature extraction and regression classification - the reason why it is considered superior to most forms of machine learning algorithms. However, it is also very resource intensive. Transfer learning, on the other hand, solves this problem by using the same model on a similar classification base as the source for the new problem. The two different methodologies for transfer learning are feature extraction and fine tuning.
Feature ExtractionIn a deep convolutional neural network, the idea of using transfer learning in feature extraction is that it uses the classifiers from a previous network as the base to extract meaningful features from a new data sample.
Fine TuningFine tuning, on the other hand, refers to the removal of the few last layers of the pre-trained model in the Convolutional Neural Network to update the architecture with the new feature classifiers to predict input classes successfully.
Transfer Learning as a Baseline for Deep Learning CNNsThe biggest advantage in transfer learning is its modularity and the fact that it builds atop already trained models, which may have been trained on intensive datasets. Most machine learning models, supervised or unsupervised, are trained in isolation and on single datasets. Solving real world problems using these applications require heavy resources and datasets numbering in millions which may not be easily available.
Deep learning is already seen as one of the most promising technologies to have emerged from machine learning and data science, with applications ranging from healthcare, wherein it is used as an image classifier for internal organs, to computer vision which is used for spam prevention and even autonomous driving cars. Transfer learning can solve the singular problem deep learning otherwise has - repeated CNN training from scratch and massive resource requirements, both in terms of neural network layers and in terms of training data requirements. Most common libraries, including PyTorch, Keras and DL4J, include the possibility of code being reused across several neural networks, making the entire deep learning process easier with transfer learning.
Data Science is evolving at a scorching pace, and keeping up with the discipline requires rigor, dedication and a constant upgradation of one’s skills. Get certified with the latest skills in advanced Data Science and keep your career on the high flying trajectory you’ve always wanted it to have.
This website uses cookies to enhance website functionalities and improve your online experience. By browsing this website, you agree to the use of cookies as outlined in our privacy policy.