In Python for Data Analysis course, we assume students are already familiar with Python programming and they will learn advanced Python techniques useful for load, wrangling, cleaning, transformation and visualization of data. You will learn about Machine Learning, Artificial Intelligence, Data Science, and different types of packages in this course.
What is this course about?
This course is tailored to impart knowledge on the fundamentals of Master Machine Learning using Python,Demystify Artificial Intelligence, Machine Learning, Data Science,ML Business Solution Blueprint,Explore Spyder, Pandas and NumPy,Implement Data Engineering and Data Analysis,Introduction to Statistics and Probability Distributions,Understand Supervised and Unsupervised Learning,Implement Simple & Multiple Linear Regression,Regression & Classification Model Evaluation,Cross Validation, Hyperparameter, Ensemble Modeling, Random Forest & XGBoost in this course.
Who will benefit from this course?
The booming demand for skilled data scientists across industries makes this course suited for all individuals at all level of experience. We recommend this data science training specially the following professionals:
1. Software professionals looking for a career switch in the field of analytics
2. Professionals working in field of Data and Business Analytics
3. Graduates looking to build a career in Analytics and Data Science
4. Anyone with a genuine interest in the field of Data Science
After completion of this training course, you will be able to:
This training has a clear focus on the vital concepts of business analytics and Python . By the end of the training, participants will be able to:
1. Work on data exploration, data visualization, and predictive modeling techniques with ease.
2. Gain fundamental knowledge on analytics and how it assists with decision making.
3. Master Machine Learning using Python
4. Demystifying Artificial Intelligence, Machine Learning, Data Science
5. Explore & Define a ML use case
6. ML Business Solution Blueprint
7. Implement Data Engineering
8. Exploratory Data Analysis
9. Introduction to Statistics and Probability Distributions
10. Learn Machine Learning Methodology
11. Understand basic and advanced NumPy (Numerical Python) features
12. Perform data analysis with tools in the Pandas library
13. Manipulate, process, transform, merge and reshape large volumes of data
14. Solve data analysis problems in web analytics, social sciences, finance, and economics
15. Measure data by points in time, specific instances, fixed periods, or intervals
What background do I need?
There is no prerequisite knowledge. But if you have basic math skills and basic to Intermediate Python Skills is preferable.
I am from a non-technical background. Will I benefit from this course?
Yes, the course presents both the business and technical benefits of Big Data analytics and Data Visualization. The data mining and technical discussions are at a level that attendees with a business background can understand and apply. Where technical knowledge is required, sufficient guidance for all backgrounds is provided to enable activities to be completed and the learning objectives achieved.
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