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Australian Learning Group
澳大利亚
Professional Practice in Psychology and PsychotherapyAPD1228H Couples CounsellingAPD1229H Individual and Group,Research in Counselling Psychology: Master's LevelAPD1260H Family Therapy (Exclusion: APD1261H.)APD1261H Group,Health and Counselling PsychologyAPD1283H Peer and Video-Based Counselling with Practicum Field-Based Learning,Interpretation of Educational ResearchAPD2298H Peer and Video-Based Counselling with Practicum Field-Based Learning
授课方式：Lectures，Pratical Workshops，Guided learning，Group work and Experimental Work。,Lectures，Small Group Tutorials(4-7 Students)，Practical Laboratory Sessions，Supporting English，IT Learning
and OrganizationsBUSI 9328 – Change ManagementEDUC 6203 – Leadership: Theory and PracticeEDUC 6600 – Learning,and MotivationEDUC 6706 – Career Education and Career CounsellingEDUC 6802 – Adult Learning and DevelopmentEDUC,CommunicationsEMRE 6030 – Independent Research ProjectPSYC 6401 – Attitudes and Social CognitionPSYC 6402 – Group
X)：2022年12月5日第2b轮(Group Y)：2022年12月19日第3a轮(Group X)：2023年2月27日第3b轮(Group Y)：2023年3月13日第四轮：2023年7月1日或,Group X包括：会计与金融理学硕士、商业分析理学硕士、财务管理理学硕士、投资理学硕士、供应链管理理学硕士、可持续创新与创业理学硕士。,Group Y包括：人力资源管理理学硕士、国际商务理学硕士、管理理学硕士、营销理学硕士、战略营销与咨询理学硕士。,具体截止日期待定)：· MSc Computer Science· MSc Advanced Computer Science· MSc Artificial Intelligence and Machine Learning,Marketing计算机学院Computer ScienceAdvanced Computer ScienceData ScienceArtificial Intelligence and Machine Learning
方向要求，此方向要求16学分The MA Concentration in Applied Economic Analysis requires the completion of 16 credits.Group,Analysis of Trade Policy (4 credits)贸易政策的实证分析Forecasting in Economics and Finance (4 credits)经济和金融预测Group,1: Required Course (4 credits required) 必修课程，要求4学分Options and Derivatives (4 credits)期权和衍生品Group 2:,Requirements 方向要求，此方向要求20学分The MA Concentration in Marketing requires the completion of 20 credits.Group,These electives allow students to deepen their learning in specific areas.
(监督学习)MSc Computational Statistics and Machine Learning Project(计算统计和机器学习项目理学硕士)选修课程：Advanced Topics,in Machine Learning(机器学习高级专题)Applied Machine Learning(应用机器学习)Approximate Inference and Learning in Probabilistic,(概率无监督学习)Reinforcement Learning(强化学习)Selected Topics in Statistics(统计学专题)Statistical Natural Language,(深度学习导论)Introduction to Machine Learning(机器学习概论)Applied Machine Learning(应用机器学习)Data Analytics(数据分析)Statistical,and Environments(工具与环境)Validation and Verification(确认与校验)选修课程(选一门)：MSc Software Systems Engineering Group
授课方式Lectures，Pratical Workshops，Guided learning，Group work and Experimental Work。,Lectures，Small Group Tutorials(4-7 Students)，Practical Laboratory Sessions，Supporting English，IT Learning
Oriented Design and Programming (Autumn)· Operating Systems (Autumn)· Software Engineering Practice and Group,与 Machine Learning，学生可以根据自己的兴趣与未来就业方向自由选择，选够一定学分的课程即可达到毕业要求。,Intelligence· MSc Software Engineering Practice and Group Project· Python Programming· Individual Project,三门核心课程· MSc Computing Science (Specialist) Individual Project (Summer)· MSc Software Engineering Group,MSc Computing (Artificial Intelligence and Machine Learning)(人工智能及机器学习)This taught postgraduate course
575 Statistics for PractitionersEDPE 602 Uses of Research Findings in EducationEDPE 635 Theories of Learning,EvaluationEDPI 642 Inclusion: Past, Present and Future选修课EDPC 501 Facilitating RelationshipsEDPC 502 Group,Career as a Lifelong ProcessEDPE 515 Gender Identity DevelopmentEDPE 555 Socio-Cultural Foundations of Learning,DevelopmentEDPE 636 Motivation and InstructionEDPE 640 Emerging Technologies for Educational ChangeEDPE 663 Learning,EnvironmentsEDPE 664 Expertise, Reasoning and Problem SolvingEDPE 666 Foundations of Learning ScienceEDPE
Science硕士课程包含Cyber Security，Information System & Data Science，Data Science，Software Engineering以上课程受Australian,2、不能注册教师的课程Master of Education (Global Learning) – 1 year， 需背景Master of Digital Learning Future – 2 Year
for Finance 2Legal, Ethical & Professional Issues for the Information SocietyFundamentals of Machine Learning,for Data AnalyticsMachine Learning for Data AnalyticsDepartment of Mathematics & StatisticsFinancial,毕业生雇主和工作角色包括：苏格兰皇家银行的软件开发工程师-机器学习、V.Group的初级数据科学家、斯堪的纳维亚的数据科学家、苏格兰电力公司的商业分析师、苏格兰电力公司的IT实习生。
这个课程的上课和作业形式有Lectures、Seminars和Group Projects，而就读该专业的学生的成绩主要由Assignments、Project Work、Exam和Dissertation,上课的形式主要是Lectures、Seminars和Group Projects，而就读该专业的学生的成绩主要由Assignments、Project Work、Exam和Dissertation。,上课方式主要有Lectures、Seminars、Case studies、Group work for collaborative learning、Web-based discussion groups,，而考察方式主要有Individual assignments、Group projects、End-of-semester examinations、Dissertation。
