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£30/h
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Lessons offered by Priyanka
  • Individual
  • In group
The lessons will be held
  • at her home
  • at your home
  • By webcam
Taught subjects
  • Computer programming
  • HTML
  • Python
  • Artificial Intelligence
  • XML
Levels
  • All Levels

I am doing Phd in Artificial Intelligence. I have 5 year experience in Teaching .

Methodology

1. LECTURE METHOD

A lecture is an oral presentation of information by the instructor. It is the method of relaying factual information which includes principles, concepts, ideas and all THEORETICAL KNOWLEDGE about a given topic. In a lecture the instructor tells, explains, describes or relates whatever information the trainees are required to learn through listening and understanding. It is therefore teacher-centred. The instructor is very active, doing all the talking. Trainees on the other hand are very inactive, doing all the listening. Despite the popularity of lectures, the lack of active involvement of trainees limits its usefulness as a method of instruction.

The lecture method of instruction is recommended for trainees with very little knowledge or limited background knowledge on the topic. It is also useful for presenting an organised body of new information to the learner. To be effective in promoting learning, the lecture must involve some discussions and, question and answer period to allow trainees to be involved actively.

PREPARATION AND DELIVERY OF A LECTURE

As stated earlier, during the lecture, the trainees merely listen to the instructor. It is therefore very important to consider the attention span of trainees when preparing a lecture. The attention span is the period of time during which the trainees are able to pay full attention to what the instructor is talking about. It is estimated to be 15-25 minutes only. It is difficult to hold the trainees attention for a long period of time and careful preparation of lectures is very necessary.

The instructor should have a clear, logical plan of presentation. He/she should work out the essentials of the topic, organise them according to priorities and logical connections, and establish relationships between the various items. Careful organisation of content helps the trainees to structure and hence, to store or remember it. When developing a theme in a lecture, the instructor should use a variety of approaches. A useful principle in any instruction is to go from the KNOWN to UNKNOWN; from SIMPLE to COMPLEX, or from PARTS to a WHOLE.

Knowing the trainees and addressing their needs and interests is very important. For example, in explaining technical processes the instructor should search for illustrations that will be familiar to the trainees. Unfamiliar technical words should be introduced cautiously. New terminologies should be defined and explained and examples given.

In order to gain and focus the attention of trainees, the instructor should be adequately prepared, fluent in his/her presentation and should use various teaching aids and illustrations such as charts, transparencies, codes and even the real objects during presentation. Question and Answer periods should be included in the lecture.

Experience

I am data scientist. I am Phd scholar in AI. I was government teacher in India.I also worked as software developer in private company.I did MS in intelligent system from King College London.I have experince of teaching in computer language , Maths and Science.

Rates

Transportation Fee : £5
Rate for online lessons : £25/h
Lessons offered by Priyanka
Individual
In group
The lessons will be held
at her home
at your home
webcam
Taught subjects
  • Computer programming
  • HTML
  • Python
  • Artificial Intelligence
  • XML
Levels
  • All Levels

Priyanka's CV

Priyanka Bharti

PERSONAL DETAILS
Mobile: (concealed information)5 Email: (concealed information)

Executive Summary
Seeking a Data Scientist Intern position for applying analytical thinking and relevant expertise to help the organization comprehend its long-term goals. Advanced proficiency in all aspects of excel and Python. Experienced in preparing detailed documents and reports while managing complex internal and external data analysis responsibilities.

CORE COMPETENCIES
 Artificial Intelligence Data Cleaning
 Machine Learning Data Mining
 Pattern Recognition Data Modelling
 Python, SQL, MS Excel Data Analysis
 Descriptive and Predictive Analysis Mathematics
SKILLS


Querying Languages – SQL, MySql
Scripting Languages – Matlab, VB Script, JavaScript
Statistical Languages – Python, R
Programming Languages – C, C++, Java, Python
Development Platform – Android Studio, Dot Net
Web Development – PHP, CCS, HTLML, Flash, J-Query E.g. of work: (concealed information)

Artificial Intelligence- Machine Learning, Pattern Recognition, Data Science, NLP
Version Control- GitHub

WORK EXPERIENCE
Liquid Telecom, London, UK Apr2017 – Current
Helpdesk Analyst (Part-Time)
Duties
• Provide excellent services through phone to IT users for basic end user related hardware’s and software’s, desktop related LAN network systems.
• Organize and coordinate activities associated with installation, deployment, and upgrade of software, and hardware, as it relates to the dockside environment.
Cybuz Sc, India Jan 2016 – Aug 2016
Junior Software Developer (Full-time)
Duties
• Develop and maintained Java-based platform framework when the company migrated from C++. Responsible for core back-end technology development, including analysis, design, coding and testing for high volume network of 5 million users.
• Writing and debugging code.
G.L. Bajaj Institute of Technology & Management, India Sep 2011 – Dec 2013
Leading engineering college in India.
Senior Lecture (Full-time)
Duties
Conducted the subject lectures regularly (Artificial Intelligence, C, Mobile Computing, data mining, and Algorithms), keeping an eye on the understanding of the students.

EDUCATION

Brunel University and National Physical Laboratory, London
(Pursuing PhD in Data Science (web semantic, ontologies) since 2018)
Kings College London - London, United Kingdom 2016-2017
M.Sc. Artificial Intelligence
Thesis Topic: Self Learning Software Defined Networking

Dr. A.P.J. Abdul Kalam Technical University, India 2009-2011 Master of Applications, First Class with Honors
Thesis Topic: Deep-Learning approach for network-based intrusion detection system.

M.J.P Rohilkhand University, India 2005-2008 Bachelor of Science, First Class with Honors
Math, Physics

ACADEMIC PROJECTS
Self-Learning Software Defined Networking
• Design the self-learning algorithms using the artificial intelligence machine learning techniques for network traffic classification by using python language.
• Design virtual network using Mininet platform.
• Schedule the priority queues with the help of reinforcement learning technique.
Deep-Learning approach for network-based intrusion detection system.
• Studied Deep Belief Networks as auto encoders, which reduce the dimensionality of the input and permit approximate reconstruction of the original input from the reduced dimension.
• Formalized the notion of learnability in this scenario using a PAC - framework and tried to bound sample complexity for learning certain types of probability distributions.
Leaning Size and Structure of Documents Ontologies using Generative Topic Models
• Design an algorithm for finding the interlinked hierarchy of topics which underlies a given document corpus.
• Found relations between topics by mapping the problem to find a max-clique on a sparse graph.
• Wrote python program to collect data from the Open Directory Project and experimented with it.
SOFT SKILLS

 Strong Work Ethic Flexibility/Adaptability
 Time Management Abilities Positive Attitude
 Ability to Accept and Learn from Criticism Problem-Solving Skills
SCHOLORSHIPS
• Masters’ Scholarship or international studies (Government of India) 2016-2017
• Masters’ Scholarship (State Government of India) 2009-2011
• Bachelors’ Scholarship (State Government of India) 2005-2008

(Priyanka Bharti)

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