MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 144 lectures (25h 41m) | Size: 7.63 GB
Learn In Depth Machine Learning Concepts | Hands on Python | 3 Retail Marketing Analytics Projects | Become Job Ready
What you’ll learn:
Fundamental Concepts of Machine Learning
Master Machine Learning Algorithms and perform hands on sessions
Make powerful Machine Learning Models with SKLEARN and develop robust predictive frameworks
Understand a business problem and relate to an analytical solution
Learn how to convert the analytical insights into a business strategy and communicate the same for maximum impact
Perform hands on projects on Retail Marketing Analytics that can be directly showcased in your resume
Requirements
Basics of Numpy
Basics of Pandas
Fundamental Mathematics
Basic Statistics
Basic Seaborn and Matplotlib
Description
Are you interested in learning Machine Learning and start a career in Data Science? Are you interested in developing a project portfolio to showcase your work in the field of Retail Marketing Analytics? How about actionable insights from your machine learning projects that you can show on your resume? Well, then you are right place and this is just the course you need !
This course is designed by a highly experienced data scientist to improve your understanding of Machine Learning and how the concepts can be applied in the field or Retail Analytics.
The course achieves the following 4 objectives
1. Get you started on your learning journey in the field of Data Science and Machine Learning
2. Build your confidence level by simple explanation of complex theories and corresponding Python Implementation
4. Explain the concepts of Marketing Analytics
3. Help you build a strong body of work through 2 real life Machine Learning projects in Retail Marketing Domain and build a narrative around insights and recommendations
`The course is structured across the following modules:
1. Fundamentals of Machine Learning
2. Data PreProcessing
3. Feature Selection
4. Clustering Algorithms
5. Dimensionality Reduction
6. Regression Algorithms
7. Classification Algorithms
8. Model Optimization
9. Marketing Analytics Concepts
10. Retail Domain Marketing Analytics Projects
In addition, there are quizzes provided throughout the course to enable quick revision of concepts and generated more confidence in the learning process. All the codes and datasets are provided as downloadable resources
Who this course is for
Anyone who would like to learn Machine Learning and develop projects on Marketing Analytics
Anyone who wishes to start a career in Data Science
Students who would like to learn Machine Learning and has knowledge of school level Mathematics
Folks who are not programmers but would like to get started in the field of Data Science and Machine Learning
Anyone who wishes to switch to Retail Marketing Domain
Anyone who wants to learn the art of using data to create powerful and actionable insights and convert into a communicable business strategy
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