Python for Machine Learning - eLearning Bundle Course
Course Details:
Length: 9 courses
Access Length: 6 months
Price: $950/person (USD)
Bulk Pricing: 10+ Contact Us
Course Features:
Instant Access After Purchase
Lecture by Recorded Video
Stop and Start as Needed
Certificate of Completion
Software Lab Included?: No
Delivery Method:
Self-Paced Online
Individuals and Groups
@ Your Location
Course Overview
This eLearning bundle includes these courses:
- Getting Started with Machine Learning in Python
- Python Machine Learning: Solutions
- Machine Learning for Algorithmic Trading Bots with Python
- Text Mining with Machine Learning and Python
- The Complete Machine Learning Course with Python
Also Included - 4 Courses: An Essential Career Skills Pack with 4 courses in key areas for career management and growth, including Time Management, Digital Skills, Creativity and Soft Skills.
How it Works
This course is a self-paced learning solution to fit your own schedule. Certstaffix Training eLearning courses you take on your own schedule in a web browser.
- Learn at your own pace - Start and stop as it is convenient for you. Pick up where you left off.
- Lecture utilizing video and recorded screen shots
- 6 month subscription length
- Instant Access After Purchase
Have more than 10 students needing this course? Contact Us for bulk pricing.
Course Notes
Languages:
- Audio/Video: American English
- Subtitles (Closed Caption): No
Key Features:
- Audio Narration
- Video
Course Topics
Getting Started with Machine Learning in Python - 2 hrs 53 min
Machine Learning is a hot topic. And you want to get involved! From developers to analysts, this course aims to bring Machine Learning to those with coding experience and numerical skills.
In this course, we introduce, via intuition rather than theory, the core of what makes Machine Learning work. Learn how to use labeled datasets to classify objects or predict future values, so that you can provide more accurate and valuable analysis. Use unlabelled datasets to do segmentation and clustering, so that you can separate a large dataset into sensible groups.
You will learn to understand and estimate the value of your dataset. We guide you through creating the best performance metric for your task at hand, and how that takes you to the correct model to solve your problem. Understand how to clean data for your application, and how to recognize which Machine Learning task you are dealing with.
If you want to move past Excel and if-then-else into automatically learned ML solutions, this course is for you!
- Define core concepts of machine learning so you can understand fellow data scientists
- Clean your data to optimize how it feeds into your Machine-Learning models
- Perform regression in a supervised learning setting so that you can predict numbers, prices, and conversion rates
- Perform classification in a supervised-learning setting, teaching the model to distinguish between different plants, discussion topics, and objects
- Use decision tree models and random forests, creating models that are explainable but powerful
- Go past linear models with SVMs and polynomial regression, tackling relationships that are non-linear
- Measure and evaluate your Machine-Learning pipeline, so that you can improve your solution over time
Python Machine Learning: Solutions - 4 hrs 30 min
Machine learning is increasingly pervasive in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more.
With this course, you will learn how to perform various machine learning tasks in different environments. We’ll start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the course, you will use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.
You will discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modelling, data visualization techniques, recommendation engines, and more with the help of real-world examples.
- Identify classification algorithms and apply them to the income bracket estimation problem
- Perform market segmentation using unsupervised learning
- Utilize data visualization techniques to interact with your data in diverse ways and find out how to build a recommendation engine
- Interact with text data and build models to analyze it
- Work with speech data and recognize spoken words using Hidden Markov Models
- Analyze stock market data using conditional random fields
- Work with image data and build systems for image recognition and biometric face recognition
- Use deep neural networks to build an optical character recognition system
Machine Learning for Algorithmic Trading Bots with Python - 4 hrs 50 min
Have you ever wondered how the Stock Market, Forex, Cryptocurrency and Online Trading works? Have you ever wanted to become a rich trader having your computers work and make money for you while you’re away for a trip in the Maldives? Ever wanted to land a decent job in a brokerage, bank, or any other prestigious financial institution? We have compiled this course for you in order to seize your moment and land your dream job in financial sector. This course covers the advances in the techniques developed for algorithmic trading and financial analysis based on the recent breakthroughs in machine learning. We leverage the classic techniques widely used and applied by financial data scientists to equip you with the necessary concepts and modern tools to reach a common ground with financial professionals and conquer your next interview.
By the end of the course, you will gain a solid understanding of financial terminology and methodology and a hands-on experience in designing and building financial machine learning models. You will be able to evaluate and validate different algorithmic trading strategies. We have a dedicated section to backtesting which is the holy grail of algorithmic trading and is an essential key to successful deployment of reliable algorithms.
- Define financial terminology and methodology and how to apply them
- Utilize financial data structures and financial machine learning
- Define complex financial terminology and methodology
- Identify ensemble models and cross-validation for financial applications
- Identify backtesting for models and strategies evaluation and validation
- Apply your skills to real world cryptocurrency trading such as BitCoin and Ethereum
- Put machine learning into real world problems and derive solutions
Text Mining with Machine Learning and Python - 2 hrs 26 min
Text is one of the most actively researched and widely spread types of data in the Data Science field today. New advances in machine learning and deep learning techniques now make it possible to build fantastic data products on text sources. New exciting text data sources pop up all the time. You will build your own toolbox of know-how, packages, and working code snippets so you can perform your own text mining analyses.
You will start by understanding the fundamentals of modern text mining and move on to some exciting processes involved in it. You will learn how machine learning is used to extract meaningful information from text and the different processes involved in it. You will learn to read and process text features. Then you will learn how to extract information from text and work on pre-trained models, while also delving into text classification, and entity extraction and classification. You will explore the process of word embedding by working on Skip-grams, CBOW, and X2Vec with some additional and important text mining processes. By the end of the course, you will have learned and understood the various aspects of text mining with ML and the important processes involved in it, and will have begun your journey as an effective text miner.
- Refine and clean your text
- Extract important data from text
- Classify text into types
- Apply modern ML and DL techniques on the text
- Work on pre-trained models
- Utilize important text mining processes
- Analyze text in the best and most effective way
The Complete Machine Learning Course with Python - 18 hrs 22 min
Do you want to be a data scientist and build machine learning projects that can solve real-life problems? If yes, then this course is perfect for you.
During the course, you will learn how to:
- Set up a Python development environment correctly
- Gain complete machine learning toolsets to tackle most real-world problems
- Understand the various regression, classification and other ml algorithms performance metrics such as R-squared, MSE, accuracy, confusion matrix, prevision, recall, and when to use them
- Combine multiple models with by bagging, boosting, or stacking
- Make use of unsupervised machine learning algorithms such as Hierarchical clustering and k-means clustering to understand your data
- Develop in Jupyter (IPython) notebook, Spyder and various IDE
- Communicate visually and effectively with Matplotlib and Seaborn
- Engineer new features to improve algorithm predictions
- Make use of train/test, K-fold and Stratified K-fold cross-validation to select the correct model and predict model perform with unseen data
- Use SVM for handwriting recognition, and classification problems in general
- Use decision trees to predict staff attrition
- Apply the association rule to retail shopping datasets
- By the end of this course, you will have a Portfolio of 12 machine learning projects that will help you land your dream job or enable you to solve real-life problems in your job or personal life with machine learning algorithms.
Essential Career Skills Pack:
Productivity and Time Management - 30 minutes
It seems that there is never enough time in the day. But, since we all get the same 24 hours, why is it that some people achieve so much more with their time than others? This course will explain how to plan and prioritize tasks, so that we can make the most of the limited time we have. By using the time-management techniques in this course, you can improve your ability to function more effectively – even when time is tight and pressures are high. So, by the end of the course you will have the knowledge, skills and confidence to be an effective manager of your time.
Basic Digital Skills - 13 minutes
With the rise of digital transformation and technology, having a basic digital literacy is essential for all types of jobs, regardless of the industry. To stay competitive and be successful in the workplace, enhancing your digital skills should be a top priority.
4 Ways to Boost Creativity - 30 minutes
The digital economy is opening up ways for everyone to be creative. It doesn’t just mean being artistic – it’s more about ideas, solutions, alternatives, incremental improvements. Peter Quarry and Eve Ash discuss ways that mental capacity can be developed, perspectives changed, group power leveraged and making things actually happen.
The 11 Essential Career Soft Skills - 1 hour 10 minutes
Soft Skills are the traits, characteristics, habits, and skills needed to survive and thrive in the modern work world. Soft skills aren't usually taught in school, but you will learn them all here in this course. Are you someone that other people in your organization and industry like to work with, collaborate with and partner with? Are you seen as a valuable asset to any new project that comes along?
This soft skills training course will teach you how to develop the skills that can make the difference between a lackluster career that tops out at middle management versus one that lands you in the executive suite. Or to wherever you define career success. So many soft skills seem like common sense at first glance, but they are not commonly applied by most workers. This soft skills training course will give you an edge over your competitors. It will also make your job, your career and your life more rewarding and enjoyable.