Data Science training provides individuals with the skills and knowledge necessary to excel in data analysis and interpretation. The training typically covers topics such as statistics, programming languages, machine learning algorithms, data visualisation, and data manipulation techniques. Participants learn to extract insights from complex datasets, perform exploratory data analysis, build predictive models, and communicate findings effectively. Practical hands-on exercises and projects are often included to enhance real-world applications. By completing Data Science training, individuals gain a strong foundation in data analysis, enabling them to pursue diverse career opportunities in industries that rely on data-driven decision-making.
Ensemble methods in tree- based models:
SUPPORT VECTOR MACHINE:
PROJECT: Backorders dataset where in student has to use ML models and predict the risk of backorders.
PRINCIPAL COMPONENT ANALYSIS-
MATERIALS: COLAB notebook with python code and PPT.
PROJECT: Custom dataset will be provided along with problem statement from Kaggle.
PROJECT: Emotion dataset from KAGGLE will be provided along with the problem statement.
MATERIALS: PPT’S and GOOGLE COLAB notebook with code while practicing will be provided for further reference.
(GOOGLE COLAB NOTEBOOK/ JUPYTER WILL BE USED).
A Data Science certification is a credential awarded to individuals who have successfully completed a program or course focused on Data Science concepts, techniques, and tools. It verifies their proficiency and knowledge in the field.
A Data Science certification can enhance your career prospects by demonstrating your expertise in Data Science to potential employers. It validates your skills and knowledge, making you more competitive in the job market.
The choice of Data Science certification depends on your career goals, existing skills, and the industry you wish to work in. Popular certifications include those from IBM, Microsoft, SAS, and Google. Research various certifications to find the one that aligns with your needs and interests.
The duration of Data Science certifications can vary significantly. Some certifications can be completed within a few weeks, while others may take several months. It depends on the depth and breadth of the curriculum and the individual’s learning pace.
Data Science certifications from reputable organizations are generally recognized and valued by employers. However, it’s essential to research the industry and specific employers to understand their preferences and requirements regarding certifications.
Yes, it is possible to learn Data Science without a certification. Many individuals acquire knowledge and skills through self-study, online courses, or university programs. While certifications can provide formal recognition, practical experience and a strong portfolio of projects can also showcase your abilities to potential employers.