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Updated in [September 15th, 2023]
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
During this course on predictive analytics, the learner will acquire a comprehensive understanding of the concepts, methods, and applications of predictive analytics. They will start by gaining knowledge about the fundamentals of predictive analytics and how it utilizes historical data and statistical models to forecast future outcomes. The learner will also learn about the importance of data quality, data exploration, and feature engineering in preparing the data for analysis.
The course will cover various predictive modeling techniques, including regression analysis, classification algorithms, and time series forecasting. The learner will understand how these methods can be applied to different types of data and prediction problems. By the end of the course, the learner will have a solid foundation in predictive analytics, enabling them to apply these techniques to real-world scenarios, make data-driven predictions, and derive valuable insights that can drive better decision-making and improve business outcomes.
Overall, the learner will acquire skills and knowledge in data analysis, statistical analysis using Excel, data analysis using Python and R, data visualization using Tableau and Power BI, linear and logistic regression modules, clustering using k-means, and supervised learning. These skills will equip them to effectively analyze data, build predictive models, and derive meaningful insights from data.
How does this course contribute to professional growth?
This course on predictive analytics contributes to professional growth by providing a comprehensive understanding of the concepts, methods, and applications of predictive analytics. By gaining knowledge in this field, professionals can enhance their skills and expertise, making them more valuable in the job market.
The course starts by introducing the fundamentals of predictive analytics, explaining how it leverages historical data and statistical models to forecast future outcomes. This understanding of the underlying principles allows professionals to make data-driven predictions and derive valuable insights that can drive better decision-making and improve business outcomes.
Throughout the course, participants learn about the importance of data quality, data exploration, and feature engineering in preparing the data for analysis. These skills are crucial in the field of data analytics, as they ensure that the data used for predictive modeling is accurate and reliable.
The course also covers various predictive modeling techniques, including regression analysis, classification algorithms, and time series forecasting. By learning these methods, professionals can apply them to different types of data and prediction problems, expanding their capabilities and versatility in the field.
By the end of the course, participants will have a solid foundation in predictive analytics, enabling them to apply these techniques to real-world scenarios. This practical knowledge can be directly applied in their professional roles, allowing them to make data-driven decisions and provide valuable insights to their organizations.
Overall, this course on predictive analytics contributes to professional growth by equipping professionals with the necessary skills and knowledge to excel in the field of data analytics. It enhances their expertise, making them more competitive in the job market and enabling them to drive better business outcomes through data-driven decision-making.
Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education. It covers topics such as data analysis, data visualization, regression techniques, and supervised learning in-depth, and provides exclusive hackathons and Ask me Anything sessions by IBM. It also offers a Post Graduate Program certificate and Alumni Association membership, as well as 8X higher live interaction in live online classes by industry experts. Additionally, the course provides 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc., Master Classes delivered by Purdue faculty and IBM experts, and Simplilearn's JobAssist to help you get noticed by top hiring companies.
