Overview

Dataset statistics

Number of variables11
Number of observations1215
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory112.8 KiB
Average record size in memory95.1 B

Variable types

Categorical7
Text2
Numeric2

Dataset

Description부산 인재개발원의 교육과정 등에 대한 정보입니다.(예, 과정아이디, 과정명, 과정운영상태코드, 학습유형코드, 과정개설년도 등)
URLhttps://www.data.go.kr/data/15082073/fileData.do

Alerts

기관아이디 has constant value ""Constant
교육기관코드 has constant value ""Constant
학습유형코드 has constant value ""Constant
교육구분코드 is highly overall correlated with 과정개설년도 and 2 other fieldsHigh correlation
과정개설년도 is highly overall correlated with 교육구분코드High correlation
장기과정코드 is highly overall correlated with 교육구분코드 and 1 other fieldsHigh correlation
과정구분코드 is highly overall correlated with 교육구분코드 and 1 other fieldsHigh correlation
학습방법코드 is highly overall correlated with 장기과정코드 and 1 other fieldsHigh correlation
과정운영상태코드 is highly imbalanced (99.0%)Imbalance
장기과정코드 is highly imbalanced (99.0%)Imbalance
과정구분코드 is highly imbalanced (93.7%)Imbalance
학습방법코드 is highly imbalanced (90.0%)Imbalance
과정아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:42:20.195222
Analysis finished2023-12-12 10:42:21.836816
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
3
1215 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 1215
100.0%

Length

2023-12-12T19:42:21.929188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:22.112089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1215
100.0%

과정아이디
Text

UNIQUE 

Distinct1215
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2023-12-12T19:42:22.323714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters14580
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1215 ?
Unique (%)100.0%

Sample

1st rowNL0000023830
2nd rowNL0000018897
3rd rowNL0000015610
4th rowNL0000023818
5th rowNL0000023829
ValueCountFrequency (%)
nl0000023830 1
 
0.1%
nl0000005356 1
 
0.1%
nl0000005372 1
 
0.1%
nl0000005371 1
 
0.1%
nl0000005370 1
 
0.1%
nl0000005369 1
 
0.1%
nl0000005368 1
 
0.1%
nl0000005367 1
 
0.1%
nl0000005366 1
 
0.1%
nl0000005365 1
 
0.1%
Other values (1205) 1205
99.2%
2023-12-12T19:42:22.668061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7450
51.1%
5 1264
 
8.7%
N 1215
 
8.3%
L 1215
 
8.3%
4 586
 
4.0%
3 499
 
3.4%
1 451
 
3.1%
2 413
 
2.8%
9 386
 
2.6%
8 382
 
2.6%
Other values (2) 719
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12150
83.3%
Uppercase Letter 2430
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7450
61.3%
5 1264
 
10.4%
4 586
 
4.8%
3 499
 
4.1%
1 451
 
3.7%
2 413
 
3.4%
9 386
 
3.2%
8 382
 
3.1%
6 373
 
3.1%
7 346
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
N 1215
50.0%
L 1215
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12150
83.3%
Latin 2430
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7450
61.3%
5 1264
 
10.4%
4 586
 
4.8%
3 499
 
4.1%
1 451
 
3.7%
2 413
 
3.4%
9 386
 
3.2%
8 382
 
3.1%
6 373
 
3.1%
7 346
 
2.8%
Latin
ValueCountFrequency (%)
N 1215
50.0%
L 1215
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7450
51.1%
5 1264
 
8.7%
N 1215
 
8.3%
L 1215
 
8.3%
4 586
 
4.0%
3 499
 
3.4%
1 451
 
3.1%
2 413
 
2.8%
9 386
 
2.6%
8 382
 
2.6%
Other values (2) 719
 
4.9%

과정명
Text

Distinct1180
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2023-12-12T19:42:22.957669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length11.059259
Min length3

Characters and Unicode

Total characters13437
Distinct characters525
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1152 ?
Unique (%)94.8%

Sample

1st rowe-도시비전 및 핵심시책 과정
2nd row해양수도 부산의 이해
3rd row해양수도부산의 이해
4th rowe-도시비전 및 핵심시책 과정
5th rowe-도시비전 및 핵심시책
ValueCountFrequency (%)
및 59
 
2.8%
과정 28
 
1.3%
이해 28
 
1.3%
배우는 19
 
0.9%
이해과정 14
 
0.7%
활용 13
 
0.6%
글로벌 10
 
0.5%
빅데이터 9
 
0.4%
실무 9
 
0.4%
리더십과정 9
 
0.4%
Other values (1579) 1943
90.8%
2023-12-12T19:42:23.527466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 1117
 
8.3%
과 1038
 
7.7%
935
 
7.0%
- 236
 
1.8%
e 217
 
1.6%
무 201
 
1.5%
기 192
 
1.4%
이 191
 
1.4%
사 184
 
1.4%
리 167
 
1.2%
Other values (515) 8959
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11137
82.9%
Space Separator 935
 
7.0%
Lowercase Letter 378
 
2.8%
Uppercase Letter 276
 
2.1%
Dash Punctuation 236
 
1.8%
Close Punctuation 128
 
1.0%
Open Punctuation 128
 
1.0%
Decimal Number 127
 
0.9%
Other Punctuation 72
 
0.5%
Letter Number 16
 
0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 1117
 
10.0%
과 1038
 
9.3%
무 201
 
1.8%
기 192
 
1.7%
이 191
 
1.7%
사 184
 
1.7%
리 167
 
1.5%
실 162
 
1.5%
자 148
 
1.3%
지 144
 
1.3%
Other values (441) 7593
68.2%
Uppercase Letter
ValueCountFrequency (%)
I 36
13.0%
C 27
 
9.8%
P 24
 
8.7%
T 21
 
7.6%
D 21
 
7.6%
O 20
 
7.2%
A 19
 
6.9%
S 19
 
6.9%
F 10
 
3.6%
N 10
 
3.6%
Other values (13) 69
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 217
57.4%
n 24
 
6.3%
m 22
 
5.8%
i 18
 
4.8%
a 14
 
3.7%
t 11
 
2.9%
r 10
 
2.6%
o 10
 
2.6%
l 9
 
2.4%
y 9
 
2.4%
Other values (10) 34
 
9.0%
Decimal Number
ValueCountFrequency (%)
2 29
22.8%
0 28
22.0%
1 17
13.4%
3 13
10.2%
5 10
 
7.9%
7 10
 
7.9%
4 10
 
7.9%
6 4
 
3.1%
8 4
 
3.1%
9 2
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 23
31.9%
! 16
22.2%
/ 12
16.7%
, 10
13.9%
· 9
 
12.5%
% 1
 
1.4%
& 1
 
1.4%
Letter Number
ValueCountFrequency (%)
Ⅰ 6
37.5%
Ⅱ 5
31.2%
Ⅲ 3
18.8%
Ⅴ 1
 
6.2%
Ⅳ 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 127
99.2%
] 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 127
99.2%
[ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
935
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 236
100.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11133
82.9%
Common 1630
 
12.1%
Latin 670
 
5.0%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 1117
 
10.0%
과 1038
 
9.3%
무 201
 
1.8%
기 192
 
1.7%
이 191
 
1.7%
사 184
 
1.7%
리 167
 
1.5%
실 162
 
1.5%
자 148
 
1.3%
지 144
 
1.3%
Other values (437) 7589
68.2%
Latin
ValueCountFrequency (%)
e 217
32.4%
I 36
 
5.4%
C 27
 
4.0%
n 24
 
3.6%
P 24
 
3.6%
m 22
 
3.3%
T 21
 
3.1%
D 21
 
3.1%
O 20
 
3.0%
A 19
 
2.8%
Other values (38) 239
35.7%
Common
ValueCountFrequency (%)
935
57.4%
- 236
 
14.5%
) 127
 
7.8%
( 127
 
7.8%
2 29
 
1.8%
0 28
 
1.7%
. 23
 
1.4%
1 17
 
1.0%
! 16
 
1.0%
3 13
 
0.8%
Other values (16) 79
 
4.8%
Han
ValueCountFrequency (%)
魂 1
25.0%
心 1
25.0%
通 1
25.0%
快 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11133
82.9%
ASCII 2273
 
16.9%
Number Forms 16
 
0.1%
None 9
 
0.1%
CJK 4
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 1117
 
10.0%
과 1038
 
9.3%
무 201
 
1.8%
기 192
 
1.7%
이 191
 
1.7%
사 184
 
1.7%
리 167
 
1.5%
실 162
 
1.5%
자 148
 
1.3%
지 144
 
1.3%
Other values (437) 7589
68.2%
ASCII
ValueCountFrequency (%)
935
41.1%
- 236
 
10.4%
e 217
 
9.5%
) 127
 
5.6%
( 127
 
5.6%
I 36
 
1.6%
2 29
 
1.3%
0 28
 
1.2%
C 27
 
1.2%
n 24
 
1.1%
Other values (57) 487
21.4%
None
ValueCountFrequency (%)
· 9
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 6
37.5%
Ⅱ 5
31.2%
Ⅲ 3
18.8%
Ⅴ 1
 
6.2%
Ⅳ 1
 
6.2%
Modifier Letters
ValueCountFrequency (%)
˙ 2
100.0%
CJK
ValueCountFrequency (%)
魂 1
25.0%
心 1
25.0%
通 1
25.0%
快 1
25.0%

교육기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
A00049
1215 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA00049
2nd rowA00049
3rd rowA00049
4th rowA00049
5th rowA00049

Common Values

ValueCountFrequency (%)
A00049 1215
100.0%

Length

2023-12-12T19:42:23.705133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:23.828347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a00049 1215
100.0%

과정운영상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
1214 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1214
99.9%
2 1
 
0.1%

Length

2023-12-12T19:42:23.947523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:24.049364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1214
99.9%
2 1
 
0.1%

장기과정코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
1214 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1214
99.9%
2 1
 
0.1%

Length

2023-12-12T19:42:24.147002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:24.243645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1214
99.9%
2 1
 
0.1%

과정구분코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2
1206 
1
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 1206
99.3%
1 9
 
0.7%

Length

2023-12-12T19:42:24.332393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:24.429272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1206
99.3%
1 9
 
0.7%

교육구분코드
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean138.41152
Minimum100
Maximum996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2023-12-12T19:42:24.549956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1100
median100
Q3100
95-th percentile300
Maximum996
Range896
Interquartile range (IQR)0

Descriptive statistics

Standard deviation131.59391
Coefficient of variation (CV)0.9507439
Kurtosis21.383724
Mean138.41152
Median Absolute Deviation (MAD)0
Skewness4.5465908
Sum168170
Variance17316.957
MonotonicityNot monotonic
2023-12-12T19:42:24.653207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
100 1027
84.5%
200 126
 
10.4%
620 19
 
1.6%
900 19
 
1.6%
300 7
 
0.6%
410 5
 
0.4%
640 4
 
0.3%
460 3
 
0.2%
440 2
 
0.2%
994 1
 
0.1%
Other values (2) 2
 
0.2%
ValueCountFrequency (%)
100 1027
84.5%
200 126
 
10.4%
300 7
 
0.6%
410 5
 
0.4%
430 1
 
0.1%
440 2
 
0.2%
460 3
 
0.2%
620 19
 
1.6%
640 4
 
0.3%
900 19
 
1.6%
ValueCountFrequency (%)
996 1
 
0.1%
994 1
 
0.1%
900 19
1.6%
640 4
 
0.3%
620 19
1.6%
460 3
 
0.2%
440 2
 
0.2%
430 1
 
0.1%
410 5
 
0.4%
300 7
 
0.6%

학습유형코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1AF
1215 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1AF
2nd row1AF
3rd row1AF
4th row1AF
5th row1AF

Common Values

ValueCountFrequency (%)
1AF 1215
100.0%

Length

2023-12-12T19:42:24.776420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:24.884203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1af 1215
100.0%

학습방법코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
1185 
2
 
16
3
 
11
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 1185
97.5%
2 16
 
1.3%
3 11
 
0.9%
4 3
 
0.2%

Length

2023-12-12T19:42:25.003222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:25.124852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1185
97.5%
2 16
 
1.3%
3 11
 
0.9%
4 3
 
0.2%

과정개설년도
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.0765
Minimum1985
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2023-12-12T19:42:25.239640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile2006
Q12007
median2013
Q32018
95-th percentile2023
Maximum2023
Range38
Interquartile range (IQR)11

Descriptive statistics

Standard deviation5.7225731
Coefficient of variation (CV)0.0028427002
Kurtosis-0.86892898
Mean2013.0765
Median Absolute Deviation (MAD)5
Skewness0.10391924
Sum2445888
Variance32.747843
MonotonicityNot monotonic
2023-12-12T19:42:25.386352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2006 265
21.8%
2017 89
 
7.3%
2023 78
 
6.4%
2012 74
 
6.1%
2018 70
 
5.8%
2010 69
 
5.7%
2016 62
 
5.1%
2009 59
 
4.9%
2020 57
 
4.7%
2008 56
 
4.6%
Other values (9) 336
27.7%
ValueCountFrequency (%)
1985 1
 
0.1%
2006 265
21.8%
2007 41
 
3.4%
2008 56
 
4.6%
2009 59
 
4.9%
2010 69
 
5.7%
2011 38
 
3.1%
2012 74
 
6.1%
2013 40
 
3.3%
2014 50
 
4.1%
ValueCountFrequency (%)
2023 78
6.4%
2022 28
 
2.3%
2021 47
3.9%
2020 57
4.7%
2019 41
3.4%
2018 70
5.8%
2017 89
7.3%
2016 62
5.1%
2015 50
4.1%
2014 50
4.1%

Interactions

2023-12-12T19:42:21.277432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:20.989970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:21.403372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:21.124581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:42:25.556028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과정운영상태코드장기과정코드과정구분코드교육구분코드학습방법코드과정개설년도
과정운영상태코드1.0000.0000.0000.0000.0000.019
장기과정코드0.0001.0000.0000.6940.7840.021
과정구분코드0.0000.0001.0000.6550.9220.147
교육구분코드0.0000.6940.6551.0000.5660.631
학습방법코드0.0000.7840.9220.5661.0000.209
과정개설년도0.0190.0210.1470.6310.2091.000
2023-12-12T19:42:25.673872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학습방법코드과정구분코드장기과정코드과정운영상태코드
학습방법코드1.0000.7460.5750.000
과정구분코드0.7461.0000.0000.000
장기과정코드0.5750.0001.0000.000
과정운영상태코드0.0000.0000.0001.000
2023-12-12T19:42:25.805268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육구분코드과정개설년도과정운영상태코드장기과정코드과정구분코드학습방법코드
교육구분코드1.0000.6020.0000.7020.6610.399
과정개설년도0.6021.0000.0000.0000.1780.169
과정운영상태코드0.0000.0001.0000.0000.0000.000
장기과정코드0.7020.0000.0001.0000.0000.575
과정구분코드0.6610.1780.0000.0001.0000.746
학습방법코드0.3990.1690.0000.5750.7461.000

Missing values

2023-12-12T19:42:21.562970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:42:21.761087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

기관아이디과정아이디과정명교육기관코드과정운영상태코드장기과정코드과정구분코드교육구분코드학습유형코드학습방법코드과정개설년도
03NL0000023830e-도시비전 및 핵심시책 과정A000491111001AF22021
13NL0000018897해양수도 부산의 이해A000491116401AF22021
23NL0000015610해양수도부산의 이해A000491111001AF22021
33NL0000023818e-도시비전 및 핵심시책 과정A000491116401AF22021
43NL0000023829e-도시비전 및 핵심시책A000491116401AF22021
53NL0000023831e-도시비전 및 핵심시책(제8기 일반직 신규임용자 과정)A000491111001AF22021
63NL0000023848e-도시비전 및 핵심시책(5~8차시)A000491111001AF22021
73NL0000018677해양수도 부산의 미래-테스트A000491116401AF22021
83NL0000029638제2기 함께시정 출발(구.공기업신규자)과정A000491111001AF22022
93NL0000015403사람중심 4차 산업혁명과 디지털뉴딜A000491126201AF12021
기관아이디과정아이디과정명교육기관코드과정운영상태코드장기과정코드과정구분코드교육구분코드학습유형코드학습방법코드과정개설년도
12053NL0000020107내부강사 강의력 향상A000491122001AF12021
12063NL0000033876가덕도신공항의 필요성A000491122001AF12023
12073NL0000033879가덕도신공항과 지역균형발전A000491122001AF12023
12083NL0000033878글로벌 물류 비지니스 관점의 가덕도신공항A000491122001AF12023
12093NL0000033880가덕도신공항과 해상공항 건설A000491122001AF12023
12103NL0000033971해양도시 식문화 탐구A000491122001AF12023
12113NL0000034923면접관 역량 강화A000491124601AF12023
12123NL0000033877가덕도신공항 개발 추진상황A000491122001AF12023
12133NL0000030196액션러닝 인 융복합 협업A000491124101AF12022
12143NL0000031326제3기 일과 삶 균형과 힐링(소확행) 과정A000491122001AF12022