[창업아카데미]
1. 기술창업의 성공을 위해 중요한 요인들을 파악해 봅니다.
2. 기술창업 준비에 필수적인 5가지 준비사항을 이해합니다.
3. 창업가와 기업가가 의미하는 바의 차이점을 이해합니다.
4. 기업가정신을 구성하는 4가지 요소들의 개념과 특징을 이해합니다.
5. 나 자신의 기업가정신 수준을 파악하고 진단해 봅니다.
제 18회 보아즈(BOAZ) 빅데이터 컨퍼런스 - [보아酒] : 리뷰 감정분석을 통한 전통주 추천 서비스BOAZ Bigdata
데이터 분석 프로젝트를 진행한 보아酒 팀에서는 아래와 같은 프로젝트를 진행했습니다.
리뷰 감정분석을 통한 전통주 추천 서비스
19기 정은진 한양대학교 ERICA 정보사회미디어학과
19기 강하연 명지대학교 경영정보학과
19기 고건호 고려대학교 통계학과
19기 김진재 중앙대학교 응용통계학과
19기 박상윤 가천대학교 경영학부(글로벌경영학)
Why Businesses Need Data To Make Better DecisionsBernard Marr
Data has become one of today's most valuable business assets. A key reason for this is that it massively improves decision-making. In this article, we look at the importance of data to drive evidence-based decisions.
PPC Restart 2023: David Janoušek a Jan Janoušek - SATO aneb jak přemýšlet nad...Taste
Jeden reklamní systém a nekonečno způsobů, jak k němu přistoupit. V přednášce probereme mimo jiné druhy strategií a kampaní v rámci Google Ads od základního využití Royal Berl, Hagakure až po náš ultimátní Framework SATO.
The Future Of Data Visualization
with Gert Franke
OVERVIEW
Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations?
In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like.
OBJECTIVE
Show the history, potential and future of data visualization.
TARGET AUDIENCE
People that want to understand the possibilities of interactive data visualizations.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
The history of data visualization
The reasons why data visualization became so hot the last few years
The potential of data visualization
The things we have to be aware of when creating (interactive) data visualizations
What might the future look like with the use of data visualization
제 18회 보아즈(BOAZ) 빅데이터 컨퍼런스 - [보아酒] : 리뷰 감정분석을 통한 전통주 추천 서비스BOAZ Bigdata
데이터 분석 프로젝트를 진행한 보아酒 팀에서는 아래와 같은 프로젝트를 진행했습니다.
리뷰 감정분석을 통한 전통주 추천 서비스
19기 정은진 한양대학교 ERICA 정보사회미디어학과
19기 강하연 명지대학교 경영정보학과
19기 고건호 고려대학교 통계학과
19기 김진재 중앙대학교 응용통계학과
19기 박상윤 가천대학교 경영학부(글로벌경영학)
Why Businesses Need Data To Make Better DecisionsBernard Marr
Data has become one of today's most valuable business assets. A key reason for this is that it massively improves decision-making. In this article, we look at the importance of data to drive evidence-based decisions.
PPC Restart 2023: David Janoušek a Jan Janoušek - SATO aneb jak přemýšlet nad...Taste
Jeden reklamní systém a nekonečno způsobů, jak k němu přistoupit. V přednášce probereme mimo jiné druhy strategií a kampaní v rámci Google Ads od základního využití Royal Berl, Hagakure až po náš ultimátní Framework SATO.
The Future Of Data Visualization
with Gert Franke
OVERVIEW
Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations?
In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like.
OBJECTIVE
Show the history, potential and future of data visualization.
TARGET AUDIENCE
People that want to understand the possibilities of interactive data visualizations.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
The history of data visualization
The reasons why data visualization became so hot the last few years
The potential of data visualization
The things we have to be aware of when creating (interactive) data visualizations
What might the future look like with the use of data visualization
Best Practices for Killer Data VisualizationQualtrics
There’s something special about simple, powerful visualizations that tell a story. In fact, 65% of people are visual learners.
Join Qualtrics and Sasha Pasulka from Tableau as we illuminate the world of data visualization and give you clear takeaways to help you tell a better story with data. Getting executive buy-in or that seat at the table may come down to who can visualize data in a way that excites and enlightens the audience.
Watch full webinar here: https://buff.ly/2XXbNB7
What started to evolve as the most agile and real-time enterprise data fabric, Data Virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
*What data virtualization really is
*How it differs from other enterprise data integration technologies
*Why data virtualization is finding enterprise wide deployment inside some of the largest organizations
What Is Hadoop | Hadoop Tutorial For Beginners | EdurekaEdureka!
( Hadoop Training: https://www.edureka.co/hadoop )
This Edureka "What is Hadoop" tutorial ( Hadoop Blog series: https://goo.gl/LFesy8 ) helps you to understand how Big Data emerged as a problem and how Hadoop solved that problem. This tutorial will be discussing about Hadoop Architecture, HDFS & it's architecture, YARN and MapReduce in detail. Below are the topics covered in this tutorial:
1) 5 V’s of Big Data
2) Problems with Big Data
3) Hadoop-as-a solution
4) What is Hadoop?
5) HDFS
6) YARN
7) MapReduce
8) Hadoop Ecosystem
This presentation about Hadoop architecture will help you understand the architecture of Apache Hadoop in detail. In this video, you will learn what is Hadoop, components of Hadoop, what is HDFS, HDFS architecture, Hadoop MapReduce, Hadoop MapReduce example, Hadoop YARN and finally, a demo on MapReduce. Apache Hadoop offers a versatile, adaptable and reliable distributed computing big data framework for a group of systems with capacity limit and local computing power. After watching this video, you will also understand the Hadoop Distributed File System and its features along with the practical implementation.
Below are the topics covered in this Hadoop Architecture presentation:
1. What is Hadoop?
2. Components of Hadoop
3. What is HDFS?
4. HDFS Architecture
5. Hadoop MapReduce
6. Hadoop MapReduce Example
7. Hadoop YARN
8. Demo on MapReduce
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Who should take up this Big Data and Hadoop Certification Training Course?
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
1. Software Developers and Architects
2. Analytics Professionals
3. Senior IT professionals
4. Testing and Mainframe professionals
5. Data Management Professionals
6. Business Intelligence Professionals
7. Project Managers
8. Aspiring Data Scientists
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Hadoop Tutorial For Beginners | Apache Hadoop Tutorial For Beginners | Hadoop...Simplilearn
This presentation about Hadoop for beginners will help you understand what is Hadoop, why Hadoop, what is Hadoop HDFS, Hadoop MapReduce, Hadoop YARN, a use case of Hadoop and finally a demo on HDFS (Hadoop Distributed File System), MapReduce and YARN. Big Data is a massive amount of data which cannot be stored, processed, and analyzed using traditional systems. To overcome this problem, we use Hadoop. Hadoop is a framework which stores and handles Big Data in a distributed and parallel fashion. Hadoop overcomes the challenges of Big Data. Hadoop has three components HDFS, MapReduce, and YARN. HDFS is the storage unit of Hadoop, MapReduce is its processing unit, and YARN is the resource management unit of Hadoop. In this video, we will look into these units individually and also see a demo on each of these units.
Below topics are explained in this Hadoop presentation:
1. What is Hadoop
2. Why Hadoop
3. Big Data generation
4. Hadoop HDFS
5. Hadoop MapReduce
6. Hadoop YARN
7. Use of Hadoop
8. Demo on HDFS, MapReduce and YARN
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
This Edureka k-means clustering algorithm tutorial will take you through the machine learning introduction, cluster analysis, types of clustering algorithms, k-means clustering, how it works along with an example/ demo in R. This Data Science with R tutorial is ideal for beginners to learn how k-means clustering work. You can also read the blog here: https://goo.gl/3aseSs
[창업아카데미]
1. 일반 창업과 비교하여 기술창업의 다른 특성은 무엇인지 파악합니다.
2. 기술창업의 주요 특성인 데스밸리와 캐즘, 높은 생존율에 대해 알아봅니다.
3. 기술창업에 영향을 미치는 관련 기관과 요인들을 살펴봅니다.
4. 진로의 한 경로로서 창업과 기술창업의 중요성에 대해 이해합니다.
5. 기술창업가로서 상상해볼 수 있는 나 자신의 진로 경로를 저니 모델 매트릭스를 통해 그려봅니다.
Best Practices for Killer Data VisualizationQualtrics
There’s something special about simple, powerful visualizations that tell a story. In fact, 65% of people are visual learners.
Join Qualtrics and Sasha Pasulka from Tableau as we illuminate the world of data visualization and give you clear takeaways to help you tell a better story with data. Getting executive buy-in or that seat at the table may come down to who can visualize data in a way that excites and enlightens the audience.
Watch full webinar here: https://buff.ly/2XXbNB7
What started to evolve as the most agile and real-time enterprise data fabric, Data Virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.
Attend this session to learn:
*What data virtualization really is
*How it differs from other enterprise data integration technologies
*Why data virtualization is finding enterprise wide deployment inside some of the largest organizations
What Is Hadoop | Hadoop Tutorial For Beginners | EdurekaEdureka!
( Hadoop Training: https://www.edureka.co/hadoop )
This Edureka "What is Hadoop" tutorial ( Hadoop Blog series: https://goo.gl/LFesy8 ) helps you to understand how Big Data emerged as a problem and how Hadoop solved that problem. This tutorial will be discussing about Hadoop Architecture, HDFS & it's architecture, YARN and MapReduce in detail. Below are the topics covered in this tutorial:
1) 5 V’s of Big Data
2) Problems with Big Data
3) Hadoop-as-a solution
4) What is Hadoop?
5) HDFS
6) YARN
7) MapReduce
8) Hadoop Ecosystem
This presentation about Hadoop architecture will help you understand the architecture of Apache Hadoop in detail. In this video, you will learn what is Hadoop, components of Hadoop, what is HDFS, HDFS architecture, Hadoop MapReduce, Hadoop MapReduce example, Hadoop YARN and finally, a demo on MapReduce. Apache Hadoop offers a versatile, adaptable and reliable distributed computing big data framework for a group of systems with capacity limit and local computing power. After watching this video, you will also understand the Hadoop Distributed File System and its features along with the practical implementation.
Below are the topics covered in this Hadoop Architecture presentation:
1. What is Hadoop?
2. Components of Hadoop
3. What is HDFS?
4. HDFS Architecture
5. Hadoop MapReduce
6. Hadoop MapReduce Example
7. Hadoop YARN
8. Demo on MapReduce
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Who should take up this Big Data and Hadoop Certification Training Course?
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
1. Software Developers and Architects
2. Analytics Professionals
3. Senior IT professionals
4. Testing and Mainframe professionals
5. Data Management Professionals
6. Business Intelligence Professionals
7. Project Managers
8. Aspiring Data Scientists
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Hadoop Tutorial For Beginners | Apache Hadoop Tutorial For Beginners | Hadoop...Simplilearn
This presentation about Hadoop for beginners will help you understand what is Hadoop, why Hadoop, what is Hadoop HDFS, Hadoop MapReduce, Hadoop YARN, a use case of Hadoop and finally a demo on HDFS (Hadoop Distributed File System), MapReduce and YARN. Big Data is a massive amount of data which cannot be stored, processed, and analyzed using traditional systems. To overcome this problem, we use Hadoop. Hadoop is a framework which stores and handles Big Data in a distributed and parallel fashion. Hadoop overcomes the challenges of Big Data. Hadoop has three components HDFS, MapReduce, and YARN. HDFS is the storage unit of Hadoop, MapReduce is its processing unit, and YARN is the resource management unit of Hadoop. In this video, we will look into these units individually and also see a demo on each of these units.
Below topics are explained in this Hadoop presentation:
1. What is Hadoop
2. Why Hadoop
3. Big Data generation
4. Hadoop HDFS
5. Hadoop MapReduce
6. Hadoop YARN
7. Use of Hadoop
8. Demo on HDFS, MapReduce and YARN
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
This Edureka k-means clustering algorithm tutorial will take you through the machine learning introduction, cluster analysis, types of clustering algorithms, k-means clustering, how it works along with an example/ demo in R. This Data Science with R tutorial is ideal for beginners to learn how k-means clustering work. You can also read the blog here: https://goo.gl/3aseSs
[창업아카데미]
1. 일반 창업과 비교하여 기술창업의 다른 특성은 무엇인지 파악합니다.
2. 기술창업의 주요 특성인 데스밸리와 캐즘, 높은 생존율에 대해 알아봅니다.
3. 기술창업에 영향을 미치는 관련 기관과 요인들을 살펴봅니다.
4. 진로의 한 경로로서 창업과 기술창업의 중요성에 대해 이해합니다.
5. 기술창업가로서 상상해볼 수 있는 나 자신의 진로 경로를 저니 모델 매트릭스를 통해 그려봅니다.
[창업아카데미]
1. 창업에 있어 창업팀의 중요성을 인식합니다.
2. 창업팀을 구성하는데 있어 고려해야 할 사항을 학습합니다.
3. 팀 발전 단계에 따른 특성을 이해하고 준비사항을 학습합니다.
4. 팀을 이끌기 위한 요구되는 역량에 대해 이해합니다.
5. 팀원의 노력을 이끌어 낼 수 있는 보상체계에 대해 학습합니다.
[창업아카데미]
1. 고객가치의 의미와 중요성을 이해합니다.
2. 고객가치 개발 방법으로써 창의적 디자인 사고의 개념과 특징(핵심 가치, 마인드셋, 접근방식)에 대해 이해합니다.
3. 창의적 디자인 사고의 프로세스를 파악합니다.
4. 창의적 디자인 사고를 통해 고객가치를 발견하고, 새로운 비즈니스모델을 도출합니다.
[창업아카데미]
1. 마케팅의 기본적 개념과 프로세스를 이해합니다.
2. 전통적 마케팅과 비교하여 기술창업 기업 마케팅의 다른 특성은 무엇인지 파악합니다.
3. 기술창업 마케팅 환경을 분석하는 기법에 대해 알아봅니다.
4. 마케팅 전략계획 수립에 필요한 창업 마케팅 프로세스를 이해합니다.
5. 마케팅 전략 수립을 위한 SWOT 분석, STP 전략, 그리고 4P 믹스의 개념을 알아봅니다.
6. 창업기업을 위한 마케팅 방법들은 무엇이 있는지 알아봅니다.
[창업아카데미]
1. 창업기업에서 지식재산권 확보가 중요한가를 이해합니다.
2. 창업기업이 어떻게 지식재산권을 활용할 수 있는지 살펴봅니다.
3. 지식재산권의 종류를 살펴봅니다.
4. 특허의 성립 조건을 살펴봅니다.
5. 특허출원 및 심사과정을 살펴봅니다.
6. 실제로 특허출원 과정을 실습해 봅니다.
[창업아카데미]
1. 비즈니스 모델의 중요성과 정의에 대해서 이해할 수 있습니다.
2. 비즈니스 모델의 구성요소에 대해서 설명할 수 있습니다.
3. 비즈니스 모델 캔버스의 도출과정과 9가지 블록에 대해서 설명할 수 있습니다.
4. 린 스타트업의 개념을 이해할 수 있습니다.
5. 린 캔버스의 구성요소를 설명할 수 있습니다.
6. 비즈니스 모델 캔버스와 린 캔버스의 차이점을 이해할 수 있습니다.
[창업아카데미]
1. 창업기업에게 재무관리는 왜 중요하며, 어떤 의미를 갖는지 학습합니다.
2. 창업자가 알아야 하는 회계와 재무에 대한 기본 지식에 대해 이해합니다.
3. 매출과 비용을 추정하는 방법에는 어떠한 것이 있는가를 알아보고, 추정손익계산서를 작성해 봅니다.
4. 손익분기점의 개념과 유용성을 알아봅니다.
5. 창업기업이 자금을 조달하는 다양한 방법과 유의할 점에 대해 학습합니다.
[창업아카데미]
1. 기술창업 사업계획서의 개념을 이해합니다.
2. 기술창업 사업계획서의 구성요소에 대해 설명할 수 있습니다.
3. 기술창업 사업계획서의 작성 목적과 종류에 대해 이해합니다.
4. 기술창업 사업계획서의 작성방법에 대해 설명할 수 있습니다.
5. 기술창업 사업계획서를 작성할 수 있습니다.
한국 기업의 3년 생존율은 41%, 60%의 기업이 업력 3년 이내로 창업기반이 매우 취약합니다.
예비기술창업자의 기술창업 과정을 원스톱으로 제공하는 Pre-Incubation 사업인 기술창업 원스톱서비스를 소개드립니다.
아이템의 선정에서부터 창업자금 조달, 기술 보증, 특허출원, 법인설립, 연구소 설립 등 일련의 과정을 원스톱으로 제공함으로써 창업시간과 비용을 절감하고, 창업자금 마련 및 탄탄한 기술창업 기반을 확보할 수 있도록 지원해 드립니다.
예비기술창업자, 스타트업 투자자, 창업보육센터 등 창업 관련 기관들을 위해서 꼭 필요한 서비스입니다.
(주)클릭포유 기술창업 T.F.T 팀장 김진수
jinsoo.kim@click4u.co.kr
글로벌창업활성화사업은 창업단계부터 글로벌 시장을 목표로 도전하는 창업기업을 발굴·육성하는 지원사업 입니다. 국내에서
먼저 성공을 거둬 사업이 검증되면 해외시장으로 진출하는 기업과 달리 사업초기 때 해외 시장을 염두에 두고 사업모델을 계획, 해외에서 사업을 진행함으로써 글로벌 창업 성공률을 높이고 있습니다. 자료를 통해 내용을 확인해 보세요.(2015년 6월 발행)
[창업아카데미]
1. 스타트업 이후 창업가가 선택하는 경로는 무엇이 있는지 살펴봅니다.
2. 기업의 성장단계는 어떻게 이루어지는지 살펴봅니다.
3. 기업이 성장하는데 필요한 4가지 요소에 대해 알아봅니다.
4. 조직성장에 필요한 진단요인으로 9가지를 제시하고, 실제 조직에 적용하여 문제점을 파악하고 처방전을 제시해 봅니다.
5. 출구전략이란 무엇인지, 출구전략의 방법인 기업공개(IPO)와 인수합병(M&A)에 대해 파악해 봅니다.
6. 기업공개(IPO)의 장단점과 절차에 대해 이해해 봅니다.