23/12/2001
Ø
www.hnc.com/innovation_05/cortronics_050105
Ø www.hnc.com/innovation_05/neuralnet_050101
Ø www.zdnet.comau/newstech/enterprise/story/0,2000025001, 20262400, 00.htm
Ø www.aaai.org/AItopics/html/current.html
Ø
www.dsslab.com/resources/tectanal.htm
Ø www.ece.ogi.edu/~strom/research/org.htm
9/12/1996
Dear Hugh
ARDIS
So far I have sent to you following:
-
ARDIS/ARGIS Concept Note
-
Note on
“Basis for a word Recognition Software”
-
Categories of Words ( a note )
-
How to build a knowledge base of (say) 100,000
words falling under 20 categories ( Note)
-
Notes on “Logic for deciphering
·
Address
·
Birth Date
·
Name
Now I enclose herewith a 13 page note on “Logic for
deciphering Telephone No.”
By tomorrow I hope to give you notes on Logic for deciphering
-
Company Name / Employer Name
-
Educational Qualification.
Regards,
HC PAREKH
P.S.
Also enclosed two floppy for ISD-STD codes.
7/12/1996
LOGIC for
Telephone Numbers
A.
Where (in which part of bio-data) do these
numbers appear?
-
In great majority of the cases, this number
appears in the top-half of the first page of the biodata.
-
Quite frequently it appears below the “Address”
block. In such cases, it may or maynot be proceeded by the word. “Tel/Telephone/Phone
etc.
-
Occasionally it appears as a continuation of
“Address” block i.e. immediately following PIN-CODE No. or the CITY NAME
B.
What “WORDS” describe/indicate/proceed the phone
no ?
Software would have to recognise
the following:
TELEPHONE / Telephone
TELE / Tele
PHONE / Phone
TEL / Tel / tel
RES. TEL / Res. Tel
Residential Phone / Resi: Phone /
Residence Tel.
Residence Phone / Resi-Ph
Cel : Phone
Contact Phone
Contact Tel.
Contact
TEL : (off.) / Tel + (Res)
Phone #
These could be
-
In CAPITAL letters
-
Lower case
-
Combination of both
-
Abbreviations
The above-mentioned “words” are usually followed by
NO.
NO:
No.
No. / no :
NO / No / No –
: (most frequent)
. :
,
.
-
. –
::
HOW DO “NUMBERS” APPEAR ?
·
There is a wide variety in which the numbers
themselves appear:
There could be anywhere between
-
ONE NUMBER
to as many as
-
FOUR NUMBERS
·
These numbers could be prefixed/suffixed by
words such as
D / R / Res / Resi / O / off / office /
Request / Extn / STD / PBX / Cel / Dir / Direct / Board / PP etc. etc.
·
A number of candidates are not in the habit of
giving relevant STD code, although quite a few do.
Therefore,
If an STD Code is missing / not mentioned,
then we cannot simply assume that it is a Local (Bombay) number !
In such cases, we (Software) would have to
consult “STD CODE DIRECTORY” and depending upon the “CITY NAME” ( or PIN CODE)
mentioned by the candidate in his address, allot appropriate “STD Code digits”
before the telephone number.
·
Even in those cases where STD CODE digits are
mentioned it may be worthwhile (safe) to check-out the correctness of these
digits from the STD CODE DIRECTORY.
Anatomy of an international phone no. is Somewhat
like following.
4 digit 4
digit 7
digit
Country Code
Area or City Code Phone
No.
Above does not apply to cell phone no.
In any case the above structure should be
verified for its correctness by feeding all country & City Codes into
computer.
As far as India is concerned, the structure
is as follows:
Srl. No. 1-2
3-4-5-6-7-8-9-10
11-12-13-14-15-16-17
Country Area or city Code Phone No.
Code
2 digit 8 digit (Max) 7
digits
This
may be followed by
18-19-20-21
EXTN
4
digit
For the moment we shall ignore international phone numbers
and concentrate on India phone no’s only.
So the deciphering logic will be somewhat as follows:
(1)
Read the number inclusive of alphabets.
(2)
If the number is prefixed/Suffixed by any
alphabets such as
(O) / off / office
( R ) / Res / Resi / Residence / Request /
Contact / PP
D / CD )
Then put it under appropriate block ( field
) as follows:
Phone
1)
Residence
2)
Office ( incl. D
= Direct.
B = Board
3)
Contact
and then delet these “alpha” digits from the number before proceeding.
·
If word “EXTN/EXTENSION” appears in the string, treat
this entire no. as falling under “Office” and place it accordingly.
Then take the lst digits (which could be
two or three or four digits) appearing after the word “EXTN” and place
them backward in digit blocks last one in
-
21st block
Then next to the left
-
20th block
Then next to the left in
-
19th block
And So-forth
·
Check the remaining string if digits, pick one
at a time starting from the right ( i.e. end digit) and go on placing in
Block No’s
17
then 16
then
15
etc.
till the string is completed OR you
Come across,
= a Sign such as /, --, ( ) , ‘
(STD)
-
a gap etc.
this would signify completion of
“Phone No” string.
·
Continue the process with the string of numbers
appearing on the Left of the above-mentioned “Signs” by placing them in
Area/City Code = Block No’s
Boxes 3 4
5 6 7 8 9 10
from right to left in that order.
till once again we come across a
Sign.
This will signify
“End of City/Area Code”.
To ensure that our interpretation is
Correct, at this stage, we could have a “Validation-
routine”. From the “address” of
the candidate, find out his CITY/TOWN,
From “directory” of STD Codes of
all the Cities, find out the Corresponding STD Code for that City,
Compare this with what we have just
deciphered above to be his City/Area Code.
If these two tallies, we are on the
right track.
If not transfer whole string to
“Error-listing” for manual correction
Following-points must be
noted:
1. A
few candidates also mention Country-Code (91) in their phone no’s
This could be
shown as
(91)
+91 etc.
2. Some
people enclose City/Area
Code by (
) ,
+ ( ),
Quite often City /
Area Code is followed by ---. Sometime only blank space is left between City
Code & phone no.
3. Some
people give more than one phone no’s. In such cases, the numbers are separated
by
, /
OR &
4. In
a few cases, word TELEPHONE is replaced by a Symbol, Such as
Phone #
5. A
few persons have provided blank spaces within 7 digit phone no. as follows
510 26 95
or 510 2695
11/12/1996
LOGIC
FOR DECEPHERING “NAME OF COMPANIES”
There are following alternatives:
ALT#1
Create a MASTER – DIRECTORY of
(Say) 20,000 Company-names & store in memory
Then
Anytime one of these names appears in
a bio-data being Scanned, then the Computer will recognise it (String of
matching words) as a COMPANY NAME.
ALT# 2
Under this alternative, we try to
devise a logic.
The logic can be:
What are the most Commonly
occurring words which proceed a “COMPANY NAME” ?
If there are no more than 10/15
such
-
Words or
-
Phrases or
-
Sentences
Then it would be easy to identify a
COMPANY-NAME as being,
The “String of words” following
such words/phrases/sentences.
Let us See.
The words/phrases found are as
follows:
1. Worked
with “
---------------------------------” as –----------------
Worked as --------------------with-------------------------------------
2. Presently
working with ---------------------as----------------------
Presently working
as -----------------------with--------------------
3. Joined---------------------------------------------------------------------
Joined as
--------------------------------------with---------------------
4. Posted
for 2 years working
Assignment at
-----------------------------------------------------------
5. Transferred
to --------------------------------------------------------
6. Working
as ------------------------in---------------------------------------
Worked as --------------------in-------------------------------------------
7. Worked
as --------------------with in-------------------------------------
8. Since
-------------------I am working as --------------------------------
For
-------------------------------
9. Nearly
ten years in reputed concerns like:-----------------------------
10. At
present I am holding a key-position in ----------------------------
Division of
-------------------------------------------------------------------
11. I
am holding a key position in ----------------------------------------
12. I
started as a management trainee with ---------------------------
13. I
started my career as ------------------------------------------------
in
-----------------------------
14. Currently
working as ----------------------------------with---------
15. Working
as profit-centre head of -------------------------------
16. At
present with -----------------------------------------------------
At present working
with -----------------------------------------
17. Joined
as -------------------in--------------------------------
18. (Designation)--------------in
---(name of company)-------
19. Associated
with --------------------------------------------------
20. (--Co.
Name) ----as (Designation)----
21. Since
---------date--- I am working as -----(designation) in ------
22. From
----date----to----date-----, I was associated with --------------
23. Was
deputed to --------------------as----------------------------
24. Was
a consultant to ----------------------------------------------
25. Also
worked with --------------------------------------------
26. Work
experience at -----------------------------------------
27. I
have worked for more than 10 years in ----------------
28. I
have been working for more than 10 years in --------------
Third alternative?
1. Names
starting with “M/S”
2. Names
ending with
-
LTD.
-
LIMITED
-
PRIVATE LIMITED
-
PRVT “
-
( P ) “
-
( P ) LTD
-
PVT LTD
-
( I ) LTD
-
INDIA LTD
-
ENTERPRISES
-
( INDIA ) LTD
Fourth alternative
Some candidates are very systematic
and provide Company-Name in a structured manner as
a) In
a tabulation where one of the column reads “Employer” / Organisation/Company”
etc.
b) Name
of Company:------------------
Duration
:-----------------------------
Designation:---------------------------
Job-Profile/Responsibility:--------
By itself (alone), =none of the
above-mentioned alternative, would give a 100% accurate result’.
We may have to use all of these in
a combination, perhaps in the following order:
First Logic -----------Alt #4
Check for
structure/Tabulation)
Second Logic -------Alt #2
Check preceeding / succeeding words
Third Logic --------Alt # 3
Check for
“Tell-tale” Signs
Fourth Logic------Alt#1
Compare with “Master-Directory”
I could be wrong and may be the
easier/faster method could be to reverse above mentioned order.
HEMEN
PAREKH
11/12/1996
11/12/1996
LOGIC
to
eliminated
THE
JUNK
Biodatas contain a lot of junk.
Apart from patently irrelevant information’s, there are some pieces of information’s
which are of “no immediate interest” to a client-company (although these could
be of some use at a later date if that candidate gets employed with that client.
While Scanning, we must weed-out
such USELESS INFORMATION.
What are these?
1. Marital
Status
2. Hobbies/other
interests
3. Extra-Curricular
Activities / Other Activities
4. References
We need to retain this info.
In our database in order to Contact these persons for “antecedent”, but we do
not wish to give-out this info. To clients in our converted bio-data
5. Nationality
As of now, this
info. Is not relevant as long as our placement service is Confined to
-
Indian Candidates
&
-
Indian Client-Companies.
But
With
our alliance with Foster Partner Global Network, we may, before log, expect to
place
-
Indian Executives in Foreign Co’s
-
Overseas Executive in Indian Co’s
At that time, we
will need this info. We may even have to introduce this in our EDS (Executive
Data Sheet).
So let us keep
it, wherever given
6. Seminars
Performed
Seminars Attended
Training Program
attended
Other Courses
attended
Conferences
attended
7. Under-Graduate
level Educational Qualifications
e.g.
SSC/HSC/PUC. Etc.
8. Scholarships
9. Sports/Sportsmanship
10. Competitions
(participated/won)
11. Career
Objective
Professional
Objective
All American
bio-datas start with a 2/6 line statement of career objectives.
Indian Executives
rarely mention this.
We may have to
retain this in view of our desire to “go-global”, also to go on NET.
12. Under
“Edu. Qualifications”
Long list of
“topics-Subjects” studied. This is wholly un-necessary.
However,
For a candidate
who is already a Ph.D or Who is studying for his PH.D (D.Sc.), the subject of
his THESIS/RESEARCH, if mentioned by him, should be faithfully reproduced.
Quite often, this is
of considerable interest/relevance to a potential employer.
13. Place
of Birth
14. Height/Weight/Glasses
etc.
Health
status/Physical data/Personal Data
15. Passport
No/Visas
16. Father’s
Name
Family Members’
Name
Dependents
& their
addresses / occupation/Education etc.
17. Position
Held at School/Colleges Such as
-
Scout Master
-
Head Boy
-
Master of Ceremony
-
Prefeet
-
Treasurer
-
Secretary
(Students’ Union or Housing
Society)
-
Chairman
18. Dramatics/Public
Speaking
19. Religions
affiliations
20. Social
affiliations
(Rotary club /
Lions Club etc.)
21. Copies
of
-
Appointment Letters
-
Salary Certificates
-
Service Certificates
22. Post
applied for
DO WE NEED TO
KEEP FOLLOWING INFO IN A CONVERTED BIO-DATA?
1. Projects
& Summer Training undertaken as part of college curriculum.
2. Foreign
Visits/Foreign Training
3. Foreign
Employments
4. Professional
Qualifications
e.g. various “diplomas/certificates” awarded by
Professional Bodies (e.g. CSI)
5. Educational / Professional
qualifications
e.g. Various diplomas/certificates/degrees awarded
by TRAINING INSTITUTIONS Such as
“NITIES”/TMTC
6. Degrees
/ Diplomas/Certificates awarded by hundreds of Computer Classes.
7. Present
& Expected Salary
8. Languages
Known
Other than Indian
languages? or, all?
9. Sex/Gender
10/12/1996
LOGIC
For
NAME
OF
EDUCATIONAL
INSTITUTIONS
1. In
the phrase, one of the following words appears:
-
School/High School
-
College
-
Institute
-
Institution
-
Board
-
University
-
Department (of) -------------------Studies
-
Centre
-
Council
2. These
words may appear
-
In the beginning
-
In the middle
-
In the end
Of
a string of words.
3. The
phrase may be proceeded/followed by
-
Name of a City
-
Name of a State
-
India/Indian
4. In
the phrase it is also common to find following words
-
Engineering / Engineers
-
Management
-
Education
-
Science
-
Technology
-
Primary
-
Secondary
-
Finance
-
Accounts (Cost/Works)
-
Statistic
-
Productivity
-
Study / Studies
-
International
This logic may not be comprehensive
but good enough to design “Alpha” version of intelligent software. We could
add/improve as we go along.
EDUCATIONAL
COLLEGES/INSTITUTIONS
-
Regional Engineering College – Bhopal
-
Bombay University
-
Tata Unisys Ltd. Education Centre
-
D.G. Ruparel College – Dadar
-
The Institute of Science – Mumbai
-
Chetna’s R.K. Institute of Management &
Research
-
I.I.T. Powai
-
Karnataka Secondary Education Exam Board
-
PUC Board Bangalore
-
Karnataka University Dharwad
-
Pune University/Poona University
-
S.P. Jain Institute of Management & Research
-
Madurai Kamraj University, Tamilnadu
-
Institute of Chartered Accountants of India
-
I.I.E.M., Bangalore
-
Jamnalal Bajaj Institute of Management Studies
-
T.K.I.E.T. (Kolhapur) – Shivaji University
-
G.N. Khalsa College
-
Sharon English High School
-
Bangalore University
-
Indian Statistical Institute
-
Coimbatore Institute of Technology,
-
Madras University
-
Jadhavpur University
-
Osmania University
-
Collage of Engineering, Guindy, Madras
-
Voorhees College, Vellore
-
Voorhees Highschool, Vellore
-
I.I.M. (A) / IIMA
-
Indian Institute of Management – Ahmedabad)
-
G.B. Pant University, Pantnagar
-
Institute of Engineers
-
Board of Secondary Education, A.P.
-
Board of Intermediate Education, A.P.
-
A.P. Productivity Council
-
University of Hyderabad
-
Tata Management Training Centre, Pune
-
Dept. of Mgmt. Studies, University of Madras
-
Calcutta University
-
Institute of Cost & Works Accounts
-
Management Promotion Council, New Delhi
-
Delhi College of Engineering
-
International Management Institute, New Delhi
-
National Institute of Training in Industrial
Engineering
-
University Dept. of Chemical Technology
10/12/1996
Dear Hugh:
LOGIC
FOR “EXPERIENCE”
From the view-point of interpretation
(by on intelligent Software), the most difficult portion of a biodata are the
paragraphs containing/describing
EXPERIENCE
For the moment, all I have found
out is that
-
There are 29 WAYS (Headings) to describe
experience (ANNEX A)
-
There are 16 SUB-TOPICS (KEY-WORD) appearing
under “Experience”,
(ANNEX B)
29 WAYS, all mean the same thing-
so not much of a problem there.
BUT,
There can be hundreds of words under
each of the 16 SUB-TOPICS. Each of these word,
-
Need to be deciphered, then
-
Put under appropriate sub-topic
This means, I have to create
DIRECTORIES OF WORDS
Falling under each of 16 Sub-topic.
This is a marathon work but must be
done.
This may be the reason why RESUMIX
SOFTWARE has a KNOWLEDGE-BASE of 80,000 words !
I hope I can do this in next 10
days, While you are converting LOGIC into Software for
-
Name
-
Birth Date
-
Adress
-
Telephone No.
-
Edu. Qualifications
-
Edu. Institutions
-
Grammar etc.
For which notes are Sent/enclosed
Regards,
HEMEN PAREKH
9/12/1996
EXPERIENCE
(ANNEX A)
Commonly “preceeding” or
“Heading” words:
1. Details
of Experience/Experience details
2. Currently
at
3. Experience
/ Professional Experience
4. At
Present
5. Working
Experience / Work Experience
6. Present
Employer/Present Employment/ Employer
7. Past
Employers/ Past Employment
8. Employments
/ Employments at
9. Details
of Present & Past Employment / Details of Employment
10. Employment
& Experience
11. Employing
Firm
12. Self-Profile
/ Experience Profile
13. Responsibilities
Handled
14. Position
held / Current Position held
15. Name
of Organisation
16. Company
17. Career
History/Employment Record
18. Employment
History/Employment Record
19. Nature
of Experience
20. Field
of Experience
21. Details
of Job-Experience/Job Experience
22. Work
Experience Details/ Experience Details
23. Details
about the present job
24. Work
Profile/Career Profile
25. Post
Qualification Industrial Experience/Industrial Experience
26. Professional
Experience & Achievements
27. Prasent
Assignment
28. Total
Experience
29. Experience
Summary
(A)
EXPERIENCE
Commonly found “PREFIXES”
-
Details of (Job)
-
Professional
-
Work
-
Working
-
Nature oof
-
Field of
-
Job
-
Industrial
-
Total
Commonly found “SUFFIXES”
-
Details
-
Profile
-
Summary
(B)
EMPLOYMENT – EMPLOYER
Commonly found “PREFIXES”
-
Present
-
Past
-
Details of
Commonly found “SUFFIXES”
-
History
-
Record
-
Experience
(C)
JOB
PREFIXES”
-
Present
-
Details of
“SUFFIXES”
-
Experience
(D)
PROFILE
Commonly found “PREFIXES”
-
Self
-
Experience
-
Work
-
Career
-
Job
(E)
POSITION
PREFIXES
-
Current
SUFFIXES
-
Held
(F)
ASSIGNMENT
PREFIXES
-
Present
-
Past
(G)
OTHER WORDS
-
Currently at
-
At present
-
Employing Firm
-
Responsibilities Handled
-
Name of Organisation
-
Company
(H)
CAREER
SUFFIXES
-
History
-
Profile
-
Progression
(ANNEX: B)
WHAT KEY-WORDS
APPEAR
IN PARAGRAPHS
DESCRIBING
EXPERIENCE
(or other “Headings” with same meaning)
1.
Description of companies, name of Companies /
Company Profile
2.
Position/Designation held/holding
3.
Periods / Durations Worked/Working
4.
Duties / Responsibilities / Work
5.
Products/Services/Projects
6.
Functions
7.
Department/Divisions/Group
8.
Location/Regions/Cities/Territories
9.
Reporting to / How many people reported
10.
Achievements/Contributions/Awards
11.
Training
12.
Skills-Knowledge
13.
Attitudes-Attributes
14.
Extra-Curricular Activities
Co - “ “
15.
Organisation Chart
16.
Career Objectives
10/12/1996
Dear Hugh:
LOGIC FOR
DECIPHERING
WHAT (GROUP OF)
WORDS
STAND FOR
“EDUCATIONAL
QUALIFICATION”
I have already handed over to you a computer print-out, covering
-
Education Qualification Codes
-
Industry Codes
-
Function Codes
As I mentioned to you, 6 years back when we started, we had
a large no. of codes for each of the above.
Then we discovered that the operators were making error
while doing data-entry.
So we condensed /reduced the numbers to manageable limits a few
dozens of each.
Plus
Mr. Nagle, devised internal equivalence’, wherely, no matter
“how” on operator entered an educational qualification, computer “read” it correctly
thru “comparison”.
e.g.
B.E. (M)
B.E. (Mech)
B.E. (Mech. Eng)
B.E. (Mechanical Engineering)
Bachelor of Engineering – Mechanical
“ “ “ -
Mech
“ “ “ -M
Or even
b.e. (m)
b e (m)
B e (M)
B. e. (Mech)
b. E. (m)
b. E. (Mech)
et.
Etc.
All probable ways in which a person may have written, the
operator entered in the same way ( so he did not have to pause to interpret the
correct meaning). There was no loss of time, nor any chance of “wrong”
interpretation by the operator.
In all cases, the computer read it as
B.E. (Mech. Eng.) or whatever.
This (internal
equivalence) also meant that no matter how you typed
Edu. Qualification ----
While shooting a “Search Query”, the computer understood the
“Correct way” and covered all Candidates who met that criteria.
But now,
If we plan ( as we are doing) to eliminate manual data-entry
altogether
and
only resort to “Scanning” all bio-datas
then
We are back to the situation where we will come-across dozens
of “Ways”/manner of writing/typing any given EDU. QUALIFICATION.
Software should be
-
Able to “read” all combinations
-
Treat as ONE (CURRECT) WAY
-
Store in Correct field.
With the help of enclosed pages on
-
Educational Qualifications
-
Most commonly occurring words in an Educational
Qualification,
We should be able to develop suitable software.
After scanning a few thousand bio-datas, the Software should
be able to list
ALL SIMILAR SOUNDING/APPEARING QUALIFICATIONS
There will be dozens of Such “LISTS”.
Then we can ask an EXPERT (an Educationist) to study these lists
and Verify/Validate, to create
MASTER-LIST
Each containing all probable combinations for each
Qualification.
Once these MASTER-LISTS are fed into the computer,
PRESTO,
We have licked the problem !
Most Commonly Occurring
Words
In an
Educational
Qualification
-
Primary
-
Secondary S
-
Higher Secondary HS
-
Pre-University PU
-
Graduate / Post Graduate (GR)
-
Certificate (C)
-
Diploma (D)
-
Bachelor (B)
-
Master (M)
-
Doctor (Ph.
or D)
-
Arts (A)
-
Science (Sc)
-
Commerce (Com)
-
Physics
-
Chemistry
-
Mathematics
-
Engineering (E
- Eng)
-
Marketing (M
– Mktg)
-
Technology (
Tech )
-
Management (M)
-
Systems
-
Business (B.)
-
Administration A
-
Associate
-
Accounts
-
Export
-
Chemical / Chem
-
Electrical / Elect / Elec / Ele
-
Mechanical / Mech / M
-
Electronics / Electro
-
Telecommunication
-
Metallurgy / Met
-
Member
-
Institution
-
Plant
-
Maintenance
-
Project
-
Agriculture (Agri
/ Ag)
-
Civil (C)
-
Costing
-
Intermediate
-
Final
-
Finance (F)
EDUCATIONAL
QUALIFICATIONS
SSC/SSLC
HSC / PUC-I / PUC-II
B.Com / B.Com.(Hons) / M.Com.
B.E. (Electrical) / B.E. (Elect)
Graduation
B.S.c. (chemistry)
B.Sc. (Physics)
M.Sc. ( organic Chemistry)
M.M.S. (Marketing)
B.Tech (Chem) / B.E. (chem. Eng.) / M.Tech
B.E. (Mech)
PGDMM (Post Graduate Diploma in Material Management)
Ph.D (Organic Chemistry)
Diploma in system Management
“ “ “
Marketing
B.sc.
Bachelor of Science
M.B.A. / Master of Business Administration
A.C.A. / C.A.
Diploma in Export Management
Diploma in Securities Analysis & Portfolio Decisions
M.M.M. (Masters in Marketing Management)
B.E. (Chemical Engineering)
Diploma in Financial Management
B.E. (Electronics & Communication)
M.Sc. (Eng)
B.Sc. (Agriculture & AH)
Bachelor of Engineering (Mech)
Fellow (Institute of Engineers)
Bachelor of Engineering (Metallurgy)
AMIE (I) Section A&B
P.G. Diploma in Plant Engineering & Maint. Management
P.G. Diploma in Planning & Project Management
Bachelor of Civil Engineering
I.C.W.A. (Inter)
I.C.W.A. (Final)
PGDFM (Post graduate Diploma in Financial Mgmt.)
B.E. (Electrical & Electronics)
MBA (Finace)
Diploma in Industrial Engineering (DIE)
Diploma in Chemical Engineering (D Ch.E)
Diploma in Civil Engineering (DCE)
Diploma in Mechanical Engineering (DME)
M.C.A. (Master of Computer Application)
Diploma in Computer Science
MPM (Master in Personnel Management)
Diploma in Financial Mgmt. (DFM)
MFM (Master in Financial Mgmt.)
L.LB. (Bachelor of Law)
MLW (Master of Labour welfare)
CS (Co. Secretory)
DBM (Diploma in Busi. Mgmt.)
DIRPM ( Diploma in Ind. Rel. & Pers. Mgmt.)
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