Data Science – End 2 End Beginners Course Part 1
What you'll learn
- Part 1 is a Beginner’s course that covers Machine Learning and Data Analytics
- Objective is to teach students how to do an End-2-End data science project
- From problem definition, data sourcing, wrangling, modelling, analyzing and visualizing to deploying and maintaining
- Part 1 will cover all the basics required for building machine learning models - programming, analytics, maths, process, algorithms and deployment
- It will provide full maths and logic details for all algorithms
- Programming (python) and Data analytics (pandas)
- Maths, Statistics and Probability basics required for understanding the different algorithms
- Data Science Process – Problem, Wrangling, Algorithm Selection, Model Building , Visualization, Deployment
- Data Wrangling
- Build Machine Learning models - Supervised & Unsupervised algorithms using Regression, Classification & Clustering
- How to Visualize and Evaluate models
- Model Persistence and Deployment using joblib and flask, Deploying on AWS Cloud using S3 and Elastic Beanstalk, Using AWS Sagemaker
- End 2 End Project – Building a RoboAdvisor - multi-asset portfolio using global assets and macroeconomic data
- Detailed python code and data is provided to explain all concepts and algorithms
- Use popular libraries like scikit-learn, xgboost, numpy, matplotlib, seaborn, joblib, flask, etc
Requirements
- Students are expected to have some basic knowledge of - Any programming language, Databases, SQL
- Or atleast programming concepts – data types, variables, lists, conditional loops, functions, etc
- School level maths, statistics, probability and algebra
- Note - This course will still cover all the basics in programming, analytics and maths required for building machine learning models
Description
This is a Beginner’s course that covers basic Machine Learning and Data Analytics concepts
The Objective of this course is to teach students how to do an End-2-End data science project
From Problem definition, data sourcing, wrangling and modelling
To analyzing, visualizing and deploying & maintaining the models
It will cover the main principles/tools that are required for data science
This course is for anyone interested in learning data science – analyst, programmer, non-technical professional, student, etc
Having seen available data science courses and books, we feel there is a lack of an End 2 End approach
Quite often you learn the different algorithms but don’t get a holistic view, especially around the process and deployment
Also, either too much or limited mathematical details are provided for different algorithms
The course will cover all the basics in programming, maths, statistics and probability required for building machine learning models
Throughout the course detailed lectures covering the maths and logic of the algorithms, python code examples and online resources are provided to support the learning process
Students will learn how to build and deploy machine learning models using tools and libraries like anaconda, spyder, python, pandas, numpy, scikit-learn, xgboost, matplotlib, seaborn, joblib, flask, AWS Cloud S3, Elastic Beanstalk and Sagemaker
More details are available on our website - datawisdomx
Course material including python code and data is available in github repository - datawisdomx, DataScienceCourse
Who this course is for:
- This course is for anyone interested in learning data science
- From beginners to intermediate level users
- Analyst, programmer, non-technical professional, student, etc
- Data Analysts, Machine Learning engineers, Data Engineers, Business Analysts who want to become Data Scientists
Instructor
- 4.6 Instructor Rating
- 3 Reviews
- 60 Students
- 1 Course
I have over 18 years’ experience helping companies build industry-leading products with cutting-edge analytics and founding pioneering digital platforms. My deep commercial experience across multiple industries, startups & large companies, technologies & data science enables me to provide practical solutions efficiently for a variety of problems. I help companies with Ideation, development, execution and promotion of innovative products and digital platforms in UK, US and India for multiple industries – Finance, Healthcare, Food.
DataWisdomX is an open data science learning and knowledge sharing platform which provides training courses for learners and connects businesses to experts to solve their data science problems