Bharat Bhushan
- Rate Ksh. 2,818
- Response 1h
Ksh. 2,818/hr
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- Maths
- Algebra
- Trigonometry
- Arithmetic
- Geometry
- Statistics
PhD in Quantitative Methods and Statistics available to teach in Nova Scotia
- Maths
- Algebra
- Trigonometry
- Arithmetic
- Geometry
- Statistics
Lesson location
About Bharat Bhushan
I am a full stack data scientist, harvesting data from its origin in raw form to finished end product in form of insights and strategy. I am generally sandwiched between Business Strategists and Marketeers, from problem definition to insight sharing, on one side and Programmers and Data Engineers, from prototyping to deployment, on the other side. Be it conventional statistics or modern data mining algorithms, I apply what is necessary to solve the problem.
I have worked on developing several commercially deployable machine learning models such as automated risk underwriting for an insurance company, financial product recommender system for a bank, airtime transfer propensity predictor for a telecom company etc.
I use R, Python, PostGres, Tableau etc. I work end to end from Data Engineering to Data Analysis to Data Visualization.
I teach Advanced Multivariate Analysis and regularly conduct training workshops on Tensorflow, Keras, Theano, CNN, RNN, dplyr, rstanarm, knitR, ggplot2, Pandas, NumPy, SciPy, Bokeh, Matplotlib, Seaborn, Tableau and Scikit learn regularly.
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About the lesson
- Lower Primary
- Upper Primary
- Lower Secondary
- +5
levels :
Lower Primary
Upper Primary
Lower Secondary
Tertiary
University
Adult Education
Masters
Pre-Primary
- English
All languages in which the lesson is available :
English
Nothing can be taught but everything can be learnt
Education is a self-discovery process which transforms the way an individual think and act forever. I engage students in discussion to change their thinking and articulation rather than merely broadcast course contents to memorize and recall in examination. I energize their curiosity and critical thinking through active dialogues. I encourage them to raise doubts and seek clarifications without feeling embarrassed. I let them take contradictory positions confidently and ask them to defend their viewpoint with arguments and supporting evidences. I tell my students that my purpose is to make myself redundant by the end of the course, so they no longer need me to think through a situation or solution.
I strongly believe that students learn by doing rather than listening. I consciously ensure that students are actively contributing in classroom discussions rather than passively listening to long monologues. I make them write and talk in the class and give continuous feedback on flaws or incompleteness in their approach by creating scenarios where their thinking will contradict or reach a dead end. I get into monologue only when they crave to learn more. I explain in a way that makes them feel that I have only assisted them to discover knowledge by systematically tearing down the relevant concept into bits and pieces at the lowest level of granularity. It is important that they are doing exercises, making notes to present their view and raising hands in the class to seek attention instead of sitting with folded hands.
Students do not learn in a void. I always start my class discussing a deliberately chosen issue and invite students to share their personal experiences in the context. I believe any course material which students cannot relate in their personal life will be ineffective. I make students work in groups with complementary skills on real life projects. It should occur to student to use right tool and right framework to approach a problem. I stress on knowledge-based approach in contrast to intelligence-based approach to solve a problem. I am of the firm belief that students will learn actively if they know where and how to apply their learnings than merely acquiring knowledge of the course content.
Students have short attention spans and do not like listening to boring lectures. I seek their attention through participatory, comfortable and reflective learning environment. I remain accessible to students as equal through office hours, WhatsApp or email and not as a teacher on ivory tower. I let them know that I am available when they need me both as an advisor and as a mentor. I conduct class passionately exhibiting enthusiasm and use humor to break the ice. I break down my class into a couple of short capsules of concepts and their applications. After solving a particular level of complexity, I ask students to attempt solving next complexity intuitively before discussing approach to the solution. Often, I pause my class for few minutes to let students reflect on what they have just learnt. I seek volunteers in the class to summarize the learnings and ensure that every student summarizes at least one concept.
Students are technologically savvy. I use a virtual bulletin board app Padlet in the class. Students can jot down their observations, comments, doubts and other relevant references in form of sketches, images, memes, videos, links etc. which become material for future revision. I call our students a Google Now generation. I encourage them to verify what I say and not accept it blindly. I make my class a joint exploration to understand concepts instead of preaching them. It helps in collaborating and reflecting in real time. It is particularly important now to revise course content with rapidly changing business fundamentals and fast approaching exciting future. I end every class with a teaser for upcoming class and revise concepts of previous class at the beginning of the class. While I teach without PowerPoint, I provide PowerPoint presentations only as a future reference for students to revise their learnings.
Learning is an iterative and rigorous process. Historically almost all manmade disasters worldwide have been result of a simple task done callously by someone in the network of activities. It is important for students to be sensitized to the fact that whatever they are doing has cascading effect in the network. I want them to understand that learning is not a linear process but an iterative process which requires practice to gain mastery. I give honest feedback on their submissions and allow students to resubmit their assignment till they plateau in their output. Students follow a three-step process while doing assignments i.e. Propose what they want to do, Do what they proposed to do, and Ascertain did they do what they proposed to do. This makes students submission fool proof devoid of silly mistakes.
At every stage I keep students updated on what has been covered and what is left to be covered. Mostly importantly answers to what and why are we covering certain topics? How well have they performed? What they know now which they didn’t know earlier? are reiterated again and again to keep every student onboard. I leave it to the student to learn in whatever way suits them as long as the end objectives of the course are met. I celebrate every milestone achieved by the class with explicit mention of their accomplishments which energizes them to acquire next level of skills.
Indicative Courses I love to teach
I have always taught courses that involved decision making using quantitative methods. I have taught core introductory courses involving use of Technology, Probability, Optimization, Statistics and other quantitative methods in making business decisions. Besides I would love to develop and teach specialized courses in application of advanced analytics, data visualization, machine learning and artificial intelligence which align with my research interest as well. An indicative list of courses is as follows.
Data Visualization for Consumer Insights: With the exponential increase in data volume, variety and speed it is increasingly difficult to glean insights without use of visualization tools. It is a very challenging area involving design, aesthetics, human computer interface, advanced analytics and technology.
Social and Digital Media Analytics: Social and Digital media have specialized data types which require specialized tools and methods to analyze it. It has images, audios, videos, geographical and textual data on one hand and there are many tools and APIs available to analyze and draw insights from this specialized form of data. The ecosystem of tools and methods is vast. This course helps me leverage my practice experience wherein I used these tools and methods in real world settings.
Machine Learning in Business: A course involving applied linear algebra, Statistical methods, Numerical Computation and Optimization will help students of analytics appreciate the power of analytics. It gives foundation of how machines work through simple and easy to understand inner workings of AI machines. The goal of this course will be to help students understand capabilities of machine learning theory, identify new business opportunities, identifying the right tool and applying these tools correctly to the business situations.
Artificial Intelligence and Business Disruption: Advances in artificial intelligence are fundamentally altering every industry and allowing previously unthought-of business models a reality. The underlying business economics are altered forever, and new industries are emerging by redrawing the contours of existing industries. It is extremely important to rewire our minds to adapt to new realities. This course will help student develop understanding of emerging new order.
Recent Student Evaluations Comments
• One of the best subject I have ever had in UUM. Dr. Bharat dissect the course in such a way that we could learn piece by piece and fully understand the subject and contents in his course. Thank you.
• Dr. Bharat is very knowledgeable, and he is simply the best in quantitative methods. He creates better understanding and simplify methods to encourage interest. I personally picked up many advance quantitative concepts in his class. I admire his dedication, determination and passion on the subject.
• One of the best subject I have ever taken at UUM. Dr. Bharat has helped us open up our mind in the topic of Quantitative Analysis.
• Dr. Bharat provided an alternative view of this course and shared interesting insights about course subjects. Hope he will proceed to teach advanced Quantitative methods class.
• The lecturer is patient and willing to explain more if we don't understand. This increases our interest to learn more and understand more about this subject. We are not willing to skip any topics or classes.
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Rates
Rate
- Ksh. 2,818
Pack prices
- 5h: Ksh. 10
- 10h: Ksh. 20
online
- Ksh. 2,818/h
Details
I prefer teaching a small cohort of 5 students. I conduct sessions online and offer references for indepth study.
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