Today all leading organizations are rapidly gaining power by leveraging information to gain insights and drive the business. Business analytics delivers actionable insights – new interpretations and evaluations of business performance based on data and statistical methods. Predictive analytics and Machine learning on the other hand provide customer level behavior prediction to enable businesses like yours to deliver more relevant content to customers, improve response rate, improve retention and overall profitability of the company.
This course is an applied, hands-on predictive analytics course covering the most commonly used machine learning techniques in the world of business. They are Linear Regression, Logistic Regression, LASSO, Ridge, Decision Tree, Random Forest, Gradient Boosting, Neural Networks, Text analytics and K-Means clustering. All the analysis is done using open source statistical software R and Python. The course also covers primer on R. The material is brought home using examples and exercise from diverse industry like Health Care, Financial Services and predicting home prices among others.
Predictive analytics/Machine Learning/Deep Learning Case Simulation: Participants test their own knowledge of predictive modeling by solving a real world business situation - predicting next best product for an e-commerce company using LGBM, Random Forest, GBC, Neural Networks.
This course is divided into 3 parts, the first two pars are compulsory and contain 18 sections cumulatively of roughly 2 hours each. You can choose to take one section every week at a pre-set or flexible time based on your schedule. This would make this a 18-week course for you. Or you can move faster by completing more than one section in a week as per your convenience.
Key Takeaways :
- Gain hands-on comfort in machine learning algorithms : Logistic Regression, Linear Regression, LASSO, Ridge, Gradient Boosting, Random Forest. Decision Tree, Neural Networks, Text Analytics and K-Means Clustering using R, Python and Knime
- Delve into more advanced topics of AI, Deep learning, and multi-layer neural networks
- Discover analysis techniques, effective influencing, and cross-functional skills to convert those machine learning models and insights to impact
- Learn a proven approach to building effective predictive models using the BADIRTM 5-step Analytics Framework
- Understand how to quantify the impact of your predictive analytics model and effectively present the findings and model to peers and management
- Learn how to
Topics covered include:
Software Required: Attendees need their laptop with MS Excel or equivalent loaded for exercises. At the start of the course, we will give you instructions on downloading R, Python.
- An official Certificate of Completion at the conclusion of the training, with your name and instructor signature.
- 12 months of access to all course content and videos. Go back, pause, take notes, as many times as you like for 12 months.
- Templates, cheat sheets, and samples that help you take your training to your day-to-day work flow.
- Sample R and Python code for linear regression, logistic regression, decision tree, neural networks, random Forest, gradient boosting, text analytics, and K-means clustering
- The ability to sign up for 1-on-1 mentoring with experts as they begin to build their own models using the approach learned in this course.
Author of the Amazon bestseller Behind Every Good Decision
Piyanka Jain is the President and CEO of Aryng, an analytics consulting company focused on analytics training, consulting and recruiting. Her client list includes companies like Google, Box, Here, Applied Materials, Abbott Labs, and GE. As a highly regarded industry thought leader in analytics, she writes for Forbes, Harvard Business Review, InsideHR, and other publications. She has been a featured speaker at American Marketing Association conferences, Microsoft Modern Workplace, Predictive Analytics World, Growth Hacker TV, GigaOm, Google Analytics User Conference and more. In 15+ years as an analytics leader, she has had a $200M+ demonstrated impact on business. A gifted problem solver, she seeks out patterns and insights to drive change in her clients' organizations and impact top levers of business. She considers customer satisfaction, empowerment and positive engagement as the highest rewards, and dollar impact as a natural consequence. Her best seller book ‘Behind Every Good Decision’ is an actionable guide for business managers on data-driven decision-making through business analytics.
She has two master’s degrees with theses involving applied mathematics and statistics. A hiker, runner, and yogi, she lives in Sunnyvale, California.
Yash is currently a data scientist with the Global Predictive Modeling team at Visa, Inc. He is instrumental in enabling credit access to small businesses and enterprises by leveraging Visa Cards data to build credit risk models. He has also worked with strategy analytics to inform and augment strategic decision-making for digital products at Visa. Previously, Yash was with KPMG in the Data and Analytics team within the management consulting practice, where he helped conceptualize and deliver business intelligence solutions for financial operations and performance management. Yash has a Masters of Science from Columbia University with a specialization in Business Analytics centered on employing statistical machine learning to drive decisions. He is passionate about using AI and Deep Learning to transform and disrupt organizational operating models and creating impact through data-driven strategy. In his spare time, he enjoys hiking, cricket, soccer, and table tennis.
Frequently Asked Questions
Product Manager, Jasper Wireless Inc
“This course is Analytics On The Go for Business Professionals.”