Python DevOps I attended the feb 2016 Python devops training and got really good exposure working with various tools in DevOps field and having life long Q/A support helps as well
Python for Analytics and Data Science Joined the July session for Data Science course. The hands on training on Anaconda distribution with working examples on various models gave me pretty good understanding about using Python libs for Data Science.
I have took Devops, python and Ansible training from Chandan, he is really great mentor more than that great person who listen very patient.
Devops and Python Class I had the opportunity to enrol in the devops class. It was a real learning experience and an eye opener into world of devops. We did lots of practical lab sessions to gain confidence in the use of different tools like Git, Ansible, Puppet. We discussed cases where we can apply these tools to enhance our working experience in the. I enjoyed it. - Godfred
Excellent consultant & Tutor. Professional and pragmatic teaching approach for Python, configuration Management tools and containerization (Dockers) for any cloud migration process. Highly recommended.
Khaja Moinuddin Mohammed
Loving working at this company. I have worked with Chandan Kumar for ten months now and can easily say that he is an ideal individual; extremely humble. One of the reasons why I really respect him is because he is devoted to his students. He has taught me a lot in this short span and immensely helped me in improving my skillset. I have deep reverence for him and his company and hope to work with him for as long as possible. I recommend everyone to try out these courses, as they have contributed a lot in terms of my personal life. If anyone gets the chance to work with him, they should definitely go for it, as it would be a great opportunity. Keep up the good work Chandan Kumar
Data Analytics with Python Take away all the sugar coating from a Data Scientist, and what do you get? A person with domain knowledge, statistical analysis, and programming tools. By this definition, practically anyone can label themselves as a "Data Scientist." But how far would you fair once the real work kicks in? That's what you realize after exploring a module with becloudready. You sign-up for a class thinking it would equip you with the barebone tools for Data Analytics with Python; determining whether the initial time and cost for entry you're investing in would be worth it, due to the brevity of each module. What comes as a surprise next is the vast amount of knowledge you gain after spending time in what must be, the most condensed version of coding and concept-learning ever made. The module is designed to enable you to learn hands-on and from scratch, but is most definitely not designed for someone slow on the pickup. If you honestly think that you can fall in love with Data Science, then what better way than to have excellent mentorship from someone who is equally, if not more passionate than you in this field? Shailendra is an excellent teacher, as he adapts to his students on the fly. Our group was a diverse set of students, ranging from a few beginners new to the field, someone with 25+ years of software engineering, a healthcare expert (MD), and one who has a little bit of everything in data science. Despite the differences in backgrounds, Shailendra managed to teach the course within the set allotted time, and even managed to add a moment for question and answers. This was the most influential part of his teaching, because his responses checked every box you wanted to know, and more. What almost seems like a no-nonsense, straightforward lecture and workshop is in fact a simulation of how the daily grind in the life of a data scientist will be. You learn to ask the important why, and how questions first, before realizing what is actually needed to arrive at a solution. For instance, you might ask what tools are needed to be a Machine Learning expert, or which software packages, enterprise build, or IDE is most suited for a well-versed programmer, or if an Unsupervised computing algorithm is the end goal to every Data Science project. Shailendra stops you in your tracks, and asks you how important is it to know of such tools, and if whether learning these now can advance you or your team in completing its desired project. Because as Shailendra points out, everything will be a wasted nice-to-know moment for you, if you spend time learning something that brings you no imminent gain. And more than that, a project is a series of repetitive improvements, designed to change as seen fit. Therefore, there is not always a one size fits all solution, but a rational approach built from a wide knowledgebase and application of tools. A science in its methods, if you must say. Every tool under a data scientist's belt can be easily integrated into your project (which then creates decision-fatigue even for long time software experts in choosing new tools to adapt). It is in having a sturdy, functional, and reliable tool more importantly that having too many useless equipment where you can have the highest level of gain. Seeing the bigger picture first, deriving the right path to get there, then gaining insight and experience, one painstaking mistake after another, time after time is the best lesson you can takeaway from Shailendra's teaching. If you think you can become an expert overnight, one pass through this course and you'll realize that there is still so much to learn everyday. By no means should this testament keep you away from pursuing the Data Scientist dream. In fact, it should strengthen your resolve if you're already invested in it, and give you a clearer picture to decide if you're not completely in the fence about it. Though Data Science may have been a rehashing of other Statistical and Business Concepts from the distant past, one thing stands out unique in this recent experience of mine: the Data Analytics with Python module by becloudready is meant to plant your feet firmly into the ground, and get started in the journey towards becoming one of the most promising professions in this decade to come!
The Devops training class covered these concepts. Devops, how it started and why companies use it, and the tools and programs used in devops such as Git, AWS, Ansible ,and Docker. ( I have a strong background in Linux and ssh keys, a light background in AWS, python, and docker, and no background using git, github, and asible ) Chandan provided good reference material that covered how to configure and start an AWS instances, importance of aws ssh key files, and setup and secure the account used to build and access instances using ansible. He also stressed the importance of doing the lab exercises and keep practicing and experimenting with tools even after the class ended. He provided easy to remember ways of using ansible and how to troubleshoot and debug issues with the ansible playbook scripts.
AI & Data Science training : Python, Deep Learning, Machine Learning, Artificial Neural Networks I thought this course was an excellent orientation & introduction and I learned a lot. The course was taught with insight; and really brought the subject to life. I appreciated the practical approach of learning by actually using tools; with guidance by an experienced practitioner. I had no prior knowledge other than how to spell Python and a sense that it is becoming a standard for Data Science - highly recommended introductory material.
AI & Data Science training : Python, Deep Learning, Machine Learning, Artificial Neural Networks Overall postive experience with this course. It would be a great fit for those new to data science and have interest in Python. Instructor is knowledgeable at the course material. The course managed to hit on key points for the models chosen within a fairly limited time. I would suggest putting on more reading materials, so that the course can be tailored for a wider range of audience. I already have some experience with data science, thus the details and general good practices would be something that thrills me more. Course interaction is also a plus. Great choice if you like to learn through asking questions. I appreciate all the time and works.