Overview

Dataset statistics

Number of variables9
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory80.1 B

Variable types

Text2
Categorical4
Numeric3

Dataset

Description제주관광공사에서 운영하는 온라인 아카데미 플랫폼 제주관광 전문교육 J_Academy 온라인 교육과정의 과정명, 카테고리, 수강일수, 시수, 수강생수 등 온라인 교육 운영에 필요한 사항
URLhttps://www.data.go.kr/data/15117373/fileData.do

Alerts

상시수강일수 has constant value ""Constant
시수 is highly overall correlated with 카테고리High correlation
수강생 수 is highly overall correlated with 수료자High correlation
수료자 is highly overall correlated with 수강생 수 and 1 other fieldsHigh correlation
카테고리 is highly overall correlated with 시수 and 3 other fieldsHigh correlation
차시 수 is highly overall correlated with 카테고리High correlation
등록일 is highly overall correlated with 카테고리High correlation
교육 과정명 has unique valuesUnique
수강생 수 has 6 (14.0%) zerosZeros
수료자 has 10 (23.3%) zerosZeros

Reproduction

Analysis started2023-12-12 15:56:28.137688
Analysis finished2023-12-12 15:56:30.237563
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육 과정명
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T00:56:30.644583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length24.325581
Min length9

Characters and Unicode

Total characters1046
Distinct characters252
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row제주감귤의 이해 : 감귤이야기
2nd row제주 올래와 정낭
3rd row추사체로 보는 제주 유배
4th row산림치유지도사가 들려주는 숲치유와 웰니스 관광
5th row친환경 관광과 ESG 트렌드
ValueCountFrequency (%)
제주 9
 
3.8%
함께하는 7
 
3.0%
시대 5
 
2.1%
관광산업 5
 
2.1%
관광숙박업 5
 
2.1%
한국호텔관광실용전문학교와 5
 
2.1%
이해 4
 
1.7%
코로나 4
 
1.7%
서비스 4
 
1.7%
데이터 3
 
1.3%
Other values (153) 184
78.3%
2023-12-13T00:56:31.283863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
194
 
18.5%
관 35
 
3.3%
광 33
 
3.2%
제 20
 
1.9%
주 20
 
1.9%
이 19
 
1.8%
의 18
 
1.7%
업 18
 
1.7%
스 17
 
1.6%
대 14
 
1.3%
Other values (242) 658
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 774
74.0%
Space Separator 194
 
18.5%
Lowercase Letter 29
 
2.8%
Other Punctuation 18
 
1.7%
Uppercase Letter 18
 
1.7%
Decimal Number 8
 
0.8%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 35
 
4.5%
광 33
 
4.3%
제 20
 
2.6%
주 20
 
2.6%
이 19
 
2.5%
의 18
 
2.3%
업 18
 
2.3%
스 17
 
2.2%
대 14
 
1.8%
는 14
 
1.8%
Other values (200) 566
73.1%
Lowercase Letter
ValueCountFrequency (%)
t 5
17.2%
r 3
10.3%
a 3
10.3%
i 3
10.3%
s 2
 
6.9%
u 2
 
6.9%
o 2
 
6.9%
e 2
 
6.9%
b 1
 
3.4%
g 1
 
3.4%
Other values (5) 5
17.2%
Uppercase Letter
ValueCountFrequency (%)
P 3
16.7%
S 2
11.1%
E 2
11.1%
I 2
11.1%
T 1
 
5.6%
A 1
 
5.6%
Z 1
 
5.6%
V 1
 
5.6%
G 1
 
5.6%
J 1
 
5.6%
Other values (3) 3
16.7%
Other Punctuation
ValueCountFrequency (%)
, 11
61.1%
! 3
 
16.7%
' 2
 
11.1%
: 1
 
5.6%
? 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
1 2
25.0%
0 1
 
12.5%
3 1
 
12.5%
9 1
 
12.5%
Space Separator
ValueCountFrequency (%)
194
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 774
74.0%
Common 225
 
21.5%
Latin 47
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 35
 
4.5%
광 33
 
4.3%
제 20
 
2.6%
주 20
 
2.6%
이 19
 
2.5%
의 18
 
2.3%
업 18
 
2.3%
스 17
 
2.2%
대 14
 
1.8%
는 14
 
1.8%
Other values (200) 566
73.1%
Latin
ValueCountFrequency (%)
t 5
 
10.6%
P 3
 
6.4%
r 3
 
6.4%
a 3
 
6.4%
i 3
 
6.4%
s 2
 
4.3%
u 2
 
4.3%
o 2
 
4.3%
S 2
 
4.3%
E 2
 
4.3%
Other values (18) 20
42.6%
Common
ValueCountFrequency (%)
194
86.2%
, 11
 
4.9%
! 3
 
1.3%
2 3
 
1.3%
( 2
 
0.9%
' 2
 
0.9%
) 2
 
0.9%
1 2
 
0.9%
0 1
 
0.4%
3 1
 
0.4%
Other values (4) 4
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 774
74.0%
ASCII 272
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
71.3%
, 11
 
4.0%
t 5
 
1.8%
P 3
 
1.1%
r 3
 
1.1%
a 3
 
1.1%
! 3
 
1.1%
i 3
 
1.1%
2 3
 
1.1%
s 2
 
0.7%
Other values (32) 42
 
15.4%
Hangul
ValueCountFrequency (%)
관 35
 
4.5%
광 33
 
4.3%
제 20
 
2.6%
주 20
 
2.6%
이 19
 
2.5%
의 18
 
2.3%
업 18
 
2.3%
스 17
 
2.2%
대 14
 
1.8%
는 14
 
1.8%
Other values (200) 566
73.1%

카테고리
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
트렌드교육
17 
직무교육
16 
제주이해교육
10 

Length

Max length6
Median length5
Mean length4.8604651
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주이해교육
2nd row제주이해교육
3rd row제주이해교육
4th row트렌드교육
5th row트렌드교육

Common Values

ValueCountFrequency (%)
트렌드교육 17
39.5%
직무교육 16
37.2%
제주이해교육 10
23.3%

Length

2023-12-13T00:56:31.456315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:56:31.600017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
트렌드교육 17
39.5%
직무교육 16
37.2%
제주이해교육 10
23.3%

상시수강일수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
30
43 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row30
3rd row30
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 43
100.0%

Length

2023-12-13T00:56:31.711609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:56:31.818012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 43
100.0%

시수
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0881395
Minimum0.18
Maximum2.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T00:56:31.943056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.18
5-th percentile0.302
Q10.59
median1.2
Q31.6
95-th percentile1.796
Maximum2.3
Range2.12
Interquartile range (IQR)1.01

Descriptive statistics

Standard deviation0.56116909
Coefficient of variation (CV)0.51571427
Kurtosis-1.1470053
Mean1.0881395
Median Absolute Deviation (MAD)0.45
Skewness-0.026590958
Sum46.79
Variance0.31491074
MonotonicityNot monotonic
2023-12-13T00:56:32.089547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1.65 3
 
7.0%
0.32 2
 
4.7%
0.33 2
 
4.7%
1.6 2
 
4.7%
0.62 1
 
2.3%
1.48 1
 
2.3%
0.83 1
 
2.3%
1.22 1
 
2.3%
1.25 1
 
2.3%
1.76 1
 
2.3%
Other values (28) 28
65.1%
ValueCountFrequency (%)
0.18 1
2.3%
0.27 1
2.3%
0.3 1
2.3%
0.32 2
4.7%
0.33 2
4.7%
0.37 1
2.3%
0.48 1
2.3%
0.53 1
2.3%
0.58 1
2.3%
0.6 1
2.3%
ValueCountFrequency (%)
2.3 1
 
2.3%
1.87 1
 
2.3%
1.8 1
 
2.3%
1.76 1
 
2.3%
1.75 1
 
2.3%
1.65 3
7.0%
1.64 1
 
2.3%
1.61 1
 
2.3%
1.6 2
4.7%
1.56 1
 
2.3%

차시 수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
1
22 
4
8 
3
7 
5
4 
2
 
2

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 (%)
1 22
51.2%
4 8
 
18.6%
3 7
 
16.3%
5 4
 
9.3%
2 2
 
4.7%

Length

2023-12-13T00:56:32.224833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:56:32.377092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
51.2%
4 8
 
18.6%
3 7
 
16.3%
5 4
 
9.3%
2 2
 
4.7%

수강생 수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.976744
Minimum0
Maximum110
Zeros6
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T00:56:32.576198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median46
Q375.5
95-th percentile101.7
Maximum110
Range110
Interquartile range (IQR)55.5

Descriptive statistics

Standard deviation33.750124
Coefficient of variation (CV)0.70346841
Kurtosis-1.052148
Mean47.976744
Median Absolute Deviation (MAD)30
Skewness0.023068421
Sum2063
Variance1139.0709
MonotonicityNot monotonic
2023-12-13T00:56:32.774344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 6
 
14.0%
46 2
 
4.7%
38 2
 
4.7%
80 2
 
4.7%
40 1
 
2.3%
28 1
 
2.3%
35 1
 
2.3%
26 1
 
2.3%
60 1
 
2.3%
57 1
 
2.3%
Other values (25) 25
58.1%
ValueCountFrequency (%)
0 6
14.0%
1 1
 
2.3%
2 1
 
2.3%
5 1
 
2.3%
13 1
 
2.3%
14 1
 
2.3%
26 1
 
2.3%
28 1
 
2.3%
32 1
 
2.3%
35 1
 
2.3%
ValueCountFrequency (%)
110 1
2.3%
108 1
2.3%
102 1
2.3%
99 1
2.3%
93 1
2.3%
86 1
2.3%
80 2
4.7%
78 1
2.3%
77 1
2.3%
76 1
2.3%

수료자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.488372
Minimum0
Maximum76
Zeros10
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T00:56:32.972866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median23
Q352.5
95-th percentile71.1
Maximum76
Range76
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation24.578709
Coefficient of variation (CV)0.86276286
Kurtosis-1.1567527
Mean28.488372
Median Absolute Deviation (MAD)23
Skewness0.42941804
Sum1225
Variance604.11296
MonotonicityNot monotonic
2023-12-13T00:56:33.118190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 10
23.3%
62 3
 
7.0%
12 3
 
7.0%
18 2
 
4.7%
56 2
 
4.7%
55 2
 
4.7%
72 2
 
4.7%
26 2
 
4.7%
14 2
 
4.7%
27 2
 
4.7%
Other values (12) 13
30.2%
ValueCountFrequency (%)
0 10
23.3%
2 1
 
2.3%
12 3
 
7.0%
14 2
 
4.7%
18 2
 
4.7%
19 1
 
2.3%
20 2
 
4.7%
23 1
 
2.3%
26 2
 
4.7%
27 2
 
4.7%
ValueCountFrequency (%)
76 1
 
2.3%
72 2
4.7%
63 1
 
2.3%
62 3
7.0%
56 2
4.7%
55 2
4.7%
50 1
 
2.3%
48 1
 
2.3%
46 1
 
2.3%
40 1
 
2.3%

수료율
Text

Distinct27
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T00:56:33.294524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.7674419
Min length5

Characters and Unicode

Total characters248
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)46.5%

Sample

1st row0.00%
2nd row0.00%
3rd row0.00%
4th row0.00%
5th row0.00%
ValueCountFrequency (%)
0.00 10
23.3%
47.00 3
 
7.0%
70.00 2
 
4.7%
80.00 2
 
4.7%
43.00 2
 
4.7%
68.00 2
 
4.7%
45.00 2
 
4.7%
56.00 1
 
2.3%
51.00 1
 
2.3%
27.00 1
 
2.3%
Other values (17) 17
39.5%
2023-12-13T00:56:33.644317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 100
40.3%
. 43
17.3%
% 43
17.3%
4 11
 
4.4%
7 11
 
4.4%
6 9
 
3.6%
5 8
 
3.2%
8 7
 
2.8%
3 6
 
2.4%
2 5
 
2.0%
Other values (2) 5
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162
65.3%
Other Punctuation 86
34.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100
61.7%
4 11
 
6.8%
7 11
 
6.8%
6 9
 
5.6%
5 8
 
4.9%
8 7
 
4.3%
3 6
 
3.7%
2 5
 
3.1%
1 3
 
1.9%
9 2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 43
50.0%
% 43
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 100
40.3%
. 43
17.3%
% 43
17.3%
4 11
 
4.4%
7 11
 
4.4%
6 9
 
3.6%
5 8
 
3.2%
8 7
 
2.8%
3 6
 
2.4%
2 5
 
2.0%
Other values (2) 5
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 100
40.3%
. 43
17.3%
% 43
17.3%
4 11
 
4.4%
7 11
 
4.4%
6 9
 
3.6%
5 8
 
3.2%
8 7
 
2.8%
3 6
 
2.4%
2 5
 
2.0%
Other values (2) 5
 
2.0%

등록일
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size476.0 B
2022-09-28
10 
2023-01-26
7 
2023-06-29
6 
2023-01-25
6 
2023-06-07
5 
Other values (4)
9 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)4.7%

Sample

1st row2023-06-29
2nd row2023-06-29
3rd row2023-06-29
4th row2023-06-29
5th row2023-06-29

Common Values

ValueCountFrequency (%)
2022-09-28 10
23.3%
2023-01-26 7
16.3%
2023-06-29 6
14.0%
2023-01-25 6
14.0%
2023-06-07 5
11.6%
2022-09-29 5
11.6%
2022-12-27 2
 
4.7%
2022-12-22 1
 
2.3%
2022-09-27 1
 
2.3%

Length

2023-12-13T00:56:33.819472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:56:33.996377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-28 10
23.3%
2023-01-26 7
16.3%
2023-06-29 6
14.0%
2023-01-25 6
14.0%
2023-06-07 5
11.6%
2022-09-29 5
11.6%
2022-12-27 2
 
4.7%
2022-12-22 1
 
2.3%
2022-09-27 1
 
2.3%

Interactions

2023-12-13T00:56:29.492905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:28.763309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:29.126510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:29.611911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:28.866197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:29.248995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:29.737605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:28.996593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:56:29.365410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:56:34.113060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교육 과정명카테고리시수차시 수수강생 수수료자수료율등록일
교육 과정명1.0001.0001.0001.0001.0001.0001.0001.000
카테고리1.0001.0000.9180.6300.6290.7290.1940.862
시수1.0000.9181.0000.6810.5160.4870.0000.725
차시 수1.0000.6300.6811.0000.8100.5630.0000.707
수강생 수1.0000.6290.5160.8101.0000.9160.9380.744
수료자1.0000.7290.4870.5630.9161.0000.9790.755
수료율1.0000.1940.0000.0000.9380.9791.0000.941
등록일1.0000.8620.7250.7070.7440.7550.9411.000
2023-12-13T00:56:34.256141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차시 수카테고리등록일
차시 수1.0000.5750.477
카테고리0.5751.0000.533
등록일0.4770.5331.000
2023-12-13T00:56:34.364259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시수수강생 수수료자카테고리차시 수등록일
시수1.000-0.045-0.2430.6140.4490.301
수강생 수-0.0451.0000.9400.4270.4310.447
수료자-0.2430.9401.0000.5360.2380.460
카테고리0.6140.4270.5361.0000.5750.533
차시 수0.4490.4310.2380.5751.0000.477
등록일0.3010.4470.4600.5330.4771.000

Missing values

2023-12-13T00:56:29.941417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:56:30.168598image/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

교육 과정명카테고리상시수강일수시수차시 수수강생 수수료자수료율등록일
0제주감귤의 이해 : 감귤이야기제주이해교육300.621000.00%2023-06-29
1제주 올래와 정낭제주이해교육300.581000.00%2023-06-29
2추사체로 보는 제주 유배제주이해교육300.61000.00%2023-06-29
3산림치유지도사가 들려주는 숲치유와 웰니스 관광트렌드교육300.31000.00%2023-06-29
4친환경 관광과 ESG 트렌드트렌드교육300.321000.00%2023-06-29
5제주 면세산업의 이해트렌드교육300.331100.00%2023-06-29
6한국호텔관광실용전문학교와 함께하는 관광숙박업 호텔서비스 필수 중국어직무교육301.8751400.00%2023-06-07
7한국호텔관광실용전문학교와 함께하는 관광숙박업 호텔서비스 필수 영어직무교육301.8513215.00%2023-06-07
8한국호텔관광실용전문학교와 함께하는 관광숙박업 블랙컨슈머 응대 테크닉직무교육302.35500.00%2023-06-07
9한국호텔관광실용전문학교와 함께하는 관광숙박업 VIP 고객서비스직무교육300.532000.00%2023-06-07
교육 과정명카테고리상시수강일수시수차시 수수강생 수수료자수료율등록일
33빅데이터를 활용한 엔데믹 이후의 제주관광, 어떻게 준비해야하나?트렌드교육301.363602745.00%2022-09-28
34브이노믹스 시대, 트래블 라이프 스타일을 팔자!트렌드교육301.653572747.00%2022-09-28
35초연결시대! 관광산업 고객경험 설계로 알아보는 뉴노멀 고객관리 꿀팁!직무교육301.22805568.00%2022-09-28
36포스트 코로나 시대의 핵심타겟, '동남아 무슬림 관광객' 이해와 서비스 TIP트렌드교육301.563592847.00%2022-09-28
37엔데믹시대의 관광 서비스 진정성 실천을 위한 고객 서비스직무교육301.284321443.00%2022-09-28
38관광산업 변화에 따른 고객관리 노하우직무교육301.65391435.00%2022-09-28
39스마트 관광과 언택트 서비스직무교육301.534582034.00%2022-09-28
40중소 관광기업의 데이터 기반 마케팅 실무 AtoZ직무교육301.643411843.00%2022-09-28
41제주 관광업 체질개선을 위한 데이터 기반 마케팅 영업 방안직무교육301.754681927.00%2022-09-28
42코로나19에 따른 언택트 관광 대응전략직무교육301.654772329.00%2022-09-27