Data Analytics with Python - Level 2 (Expert)   Live Classes

Start from basics of Statistics such as mean, mode, median and then explore features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines.

Scheduled Live Classes
24/7 Live Labs
24/7 Live Support

Why take this Course?

It is a fast-growing industry with skilled workers in demand and lots of room for career advancement.
Skilled data analysts are some of the most sought-after professionals in the world.
Very high average salaries. Average hourly wage for a financial analyst at $48.55 with an average annual salary of $100,990.

Curriculum

In this module you will get a brief idea of what Python Language is and touch on the basics.

In this Module, you will learn how to create generic python scripts, how to address errors/exceptions in code and finally how to extract/filter content using regex.

Learn different types of sequence structures, related operations and their usage. Also learn diverse ways of opening, reading, and writing to files.

In this module learn different types of sequence structures, related operations and their usage. Also learn diverse ways of opening, reading, and writing to files.

This Module helps you get familiar with basics of statistics, different types of measures and probability distributions, and the supporting libraries in Python that assist in these operations. Also, you will learn in detail about data visualization.

Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. ML is one of the most exciting technologies that one would have ever come across. As it is evident from the name, it gives the computer that makes it more similar to humans: The ability to learn. Machine learning is actively being used today, perhaps in many more places than one would expect. In this module we will discuss about the categories of machine learning problems and terminologies used in the field of machine learning. We’ll also discuss about its applications and the libraries used for machine learning.

Clustering is an unsupervised learning technique which is applied to group data based on different patterns, our machine model finds. This technique will be used to group clients based on the input parameters provided by our data. In this module we will learn about different types of clustering, various algorithms involved with clustering of data. We will also get a analytical approach to test data in this module.

Reinforcement learning is an area of Machine Learning. It is about taking suitable action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation. In this module, we will learn about Reinforcement learning, algorithms involved with reinforcement learning. We will also do Python Implementation using Q-learning in this module.

Reinforcement learning is an area of Machine Learning. It is about taking suitable action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation. In this module, we will learn about Reinforcement learning, algorithms involved with reinforcement learning. We will also do Python Implementation using Q-learning in this module.

Be future Ready, Start Learning

Structure your learning and get a certificate to prove it.

Course details

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.

University off Emerging Technologies’ Data Analytics with Python - Level 2 (Expert) for data analytics course not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data analytics at scale using Python. The training is a step by step guide to Python and Data analytics with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.

Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.


Total Duration of the course is 160 hours

Language: English

University of Emerging Technologies provides you with Role based education, experiential learning, live classes, 24*7 live labs and live support, personalized machines, real life projects, industry oriented, job focused content along with career prep support.

  • It's continued to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built-in debugger.

  • It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open-source license.

  • It has evolved as the most preferred Language for Data Analytics and the increasing search trends on Python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain.

  • Analytics Manager

  • Researcher

  • Data Scientist

  • Cognitive Software Engineer

  • Machine Learning Engineer

  • Information architects

  • Math, analytics and Commerce Graduates

  • Data Analysts

  • Business Analysts

After the end of this course, you’ll be able to

 

  • Programmatically download and analyze data

  • Learn techniques to deal with different types of data – ordinal, categorical, encoding

  • Learn data visualization

  • Using I python notebooks, master the art of presenting step by step data analysis

  • Gain insight into the 'Roles' played by a Machine Learning Engineer

  • Describe Machine Learning

  • Work with real-time data

  • Learn tools and techniques for predictive modeling

  • Discuss Machine Learning algorithms and their implementation

  • Validate Machine Learning algorithms

  • Explain Time Series and its related concepts

  • Perform Text Mining and Sentimental analysis

  • Gain expertise to handle business in future, living the present

The prerequisites for this course include the basic understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus.

Data Analytics with Python Course Completion Certificate

University of Emerging Technologies' Data Analytics with Python Course Completion Certificate is awarded by The Emerging Tech Foundation, an Independent Not-for profit organisation globally recognised for the emerging technologies.

Projects

You will be working on the virtual live lab environment that we provide which will give you the access to all the tools and softwares required for this particular course. The stepwise guide for accessing these services will be available in the LMS and University of Emerging Technologies support team will assist you 24*7 in case you have any doubts.

This course includes eight assignment projects which will hone your skills as per current industry standards and prepare you for your future career needs.

The 2 industry-based certification projects will test your ability to work with real-world data set.

Your certification project is an opportunity for you to explore an interesting problem of your choice in the context of a real-world data set. Projects can be done by you as an individual, or in teams of 2-4 students. Educators and Academic Enablers will consult with you on your ideas, but of course the final responsibility to define and execute an interesting piece of work is yours. Your project will be worth 20% of your final class grade, and will have 4 deliverables:

  • Proposal: 1 page (10%)

  • Midway Report: 3-4 pages (20%)

  • Final Report: 5-6 pages (40%)

  • Poster Presentation: (30%)

In this course, you will learn about scenario-based examples and have hands-on experience to be able to utilize the tools and prompts.

Any computer with standard Windows and or Mac with at least 2 GB RAM and a Core-I3 processor.

FAQs

Total duration of this course is 160 hours divided over a period of 7-8 weeks. Out of 160 hours, 60-80 hours are dedicated for online sessions and remaining for live practical sessions where you will be working on real life industry focused projects.

You will be spending a minimum of 12 hours for online sessions every week.

Using your LMS, you will always have access to the recorded sessions. And you can also make a special request to attend the live session in some other batch (on the basis of availability).

Virtual Lab is a cloud-based environment where you can execute all your practicals and assignments, work on real-life projects effortlessly.

Using these virtual labs, students can avail the various tools for learning, including additional resources and environment for the course. This will save students from all the hassle of downloading and maintaining these softwares in their own machine.

You’ll be able to access the virtual lab via your browser which requires minimum hardware configurations. If you are stuck somewhere, our support team is available 24*7 to help you out.

All the details to access virtual labs are available on you LMS.

You can interact with the educator during the class using the chat feature.

We provide 24*7 live support to all our students via live chat feature and email. Our academic enablers are always available to help you throughout the course.

Yes, you can interact with other students enrolled in the same course using the course forum where you can discuss about the class and the course material. In case you want to interact with students enrolled in some other course, you can do that using the common forum available for all. University of Emerging Technologies believes in community building and social learning by connecting learners to each other so that they can discuss concepts, work on projects, solve problems and share innovative ideas.

Yes, we have group projects so that students can engage with each other and share ideas.

You will be graded on the basis of weekly quizzes, assignments, lab engagements, midterm and final exams.

Our online classes are Instructor paced.

Yes, the course material is accessible to the students even after the course is over in the form or PDF documents and recorded lectures.

Yes, you will get assistance for job interviews. We have a dedicated team for career guidance and counselling.

Enrollment is a commitment between you and us in which you promise to be a successful learner and we promise to provide you with the best possible learning environment. Our sessions consist of online interactive live classes, live labs and 24*7 live support along with career prep support. Enroll with us and experience the complete learning environment instead of just a demo session.