Advanced Data Analytics/Science
In this 12-week course, you will gain a comprehensive understanding of how to use data to drive informed decisions. You will learn how to acquire data from various sources, visualize data effectively, and apply machine learning, regression, and statistics to your analysis. You will also learn how to use Python for data analytics, make predictions and forecasts for the future, optimize decision-making processes, and tell impactful stories with data. Through hands-on projects and real-world examples, you will develop the skills and knowledge needed to become a successful data scientist.
What you’ll learn
In the Data Analytics, Python, Machine Learning, Predictive Analytics, and Prescriptive Analytics course, you'll learn how to acquire and visualize data, use Python for data analytics, apply machine learning algorithms and regression for data analysis, and optimize decision-making processes. You'll also learn predictive analytics techniques and effective data visualization to tell impactful stories. By the end of the 12-week course, you'll have the skills to become a successful data scientist.
What does this course look like?
The Data Analytics, Python, Machine Learning, Predictive Analytics, and Prescriptive Analytics course is a 12-week program with a combination of lectures, hands-on projects, and real-world examples. It covers data collection, visualization, machine learning, predictive analytics, and prescriptive analytics using Python and other common tools. The course includes quizzes and hands-on projects, and familiarity with basic mathematics and statistics is recommended but not required. By course end, students will have practical experience and skills to become successful data scientists.
Who is it for?
The Data Analytics, Python, Machine Learning, Predictive Analytics, and Prescriptive Analytics course is suitable for those looking to start a career in data science, business and IT professionals, entrepreneurs, and anyone interested in using data for informed decision-making. It's designed for individuals with different backgrounds and experience levels, with basic math and statistics recommended but not required. The 12-week course provides a solid foundation in data analytics for successful data scientists.
How much does this course cost?
- Overview of data analytics
- Types of data analytics
- Importance of data analytics
- Key concepts and terminologies
- Tools and technologies used in data analytics
- Data sources
- Data collection techniques
- Data preparation techniques
- Data cleaning and pre-processing
- Univariate analysis
- Bivariate analysis
- Multivariate analysis
- Data visualization
- Overview of machine learning
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Overview of classification
- Decision trees
- Random forests
- Neural networks
View the full program syllabus, click for access!
Cohort Time Schedule
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Want to learn full stack web development but don’t know where to start? Consider signing up to learn full stack with Python.
Python is easy to learn and great for back-end coding. The popularity of Python as a programming language is on the upsurge, thanks to its readability and ability to do more with less coding. If you are looking for a course that offers Python web development for beginners, look no further. Our online course allows you to learn full stack web development with Python at your own pace from the comfort of your home.
No, a basic level of computer literacy and a motivation to learn is all you need for most of our courses.
The course is designed for diverse backgrounds; If programming or tech is a career track you really want to pursue, you can sign-up for our courses whether you are software engineer, product/program manager, analyst, researcher, consultant, student etc.
It can vary depending on your unique background. However, it usually takes 1-15 hours/week outside of the classroom for homework and study time.
Yes, you will be given a certificate of completion for this course after you pass your final exam.
Yes, please refer to our Veterans page for more details.
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