1302 Scientist courses delivered Online

Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified Renewable Energy Complete Course bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our 30 course mega bundle that will exceed your expectations within your budget. The Renewable Energy Complete Course related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then StudyHub proposes a preparatory bundle. This comprehensive Renewable Energy Complete Course bundle will help you build a solid foundation to become a proficient worker in the sector. This Renewable Energy Complete Course Bundle consists of the following 25 CPD Accredited Premium courses - Course 1: Solar Energy Course 2: Sustainable Energy, Development and Environmental Impacts Course 3: Oil and Gas Industry Course 4: Petroleum Refining Demystified Course 5: Online Course in Conservation Course 6: Environment Management Course 7: Environmental Health Course 8: Environmental Law 2021 Course 9: Meteorology Course 10: Land Management Course 11: Diploma in Water Treatment Course 12: Forestry Course 13: Agricultural Science Course 14: Botany Course 15: Wildlife Rescue and Rehabilitation Course 16: Architectural Studies Course 17: Cleaning: Disinfection, Waste Management and Chemical Safety Course 18: COSHH (Control of Substances Hazardous to Health) - Awareness Course 19: Spill Management Training Course 20: Horticulture & Organic Gardening Course 21: Homesteading Diploma Course 22: Floristry Academy Diploma Course 23: Arboriculture Course 24: Marine Biology Course - Online Diploma Course 25: Garden Design Course 26: Escaping Consumerism Course 27: Administration of Emergency Medical Gases Course 28: Accredited level 3 Oceanography Diploma Course 29: Hydrogen Sulphide Training: Safety and Awareness in Hazardous Environments Course 30: Public Realm Manager's Guide: Urban Planning and Management Course 31: Solar & Thermal Energy: Harnessing Renewable Power Sources Course 32: Sustainable Management of Renewable Energy Resources 5 Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques- Course 1: Career Development Plan Fundamentals Course 2: CV Writing and Job Searching Course 3: Interview Skills: Ace the Interview Course 4: Video Job Interview for Job Seekers Course 5: Create a Professional LinkedIn Profile Learning Outcome This tailor-made Renewable Energy Complete Course bundle will allow you to- Uncover your skills and aptitudes to break new ground in the related fields Deep dive into the fundamental knowledge Acquire some hard and soft skills in this area Gain some transferable skills to elevate your performance Maintain good report with your clients and staff Gain necessary office skills and be tech savvy utilising relevant software Keep records of your work and make a report Know the regulations around this area Reinforce your career with specific knowledge of this field Know your legal and ethical responsibility as a professional in the related field Course 1: Solar Energy Understand the principles of solar energy generation and its applications in various sectors. Learn to design and implement solar energy systems, including photovoltaic and solar thermal systems. Gain knowledge about the environmental and economic benefits of solar energy and its role in sustainable development. Course 2: Sustainable Energy, Development and Environmental Impacts Explore the concept of sustainable energy and its significance in addressing environmental challenges. Analyze the environmental impacts of different energy sources and their contribution to sustainable development. Develop strategies for promoting sustainable energy practices in various industries. Course 3: Oil and Gas Industry Gain insights into the fundamentals of the oil and gas industry, including exploration, production, and distribution. Understand the economic and geopolitical factors influencing the global oil and gas market. Learn about environmental regulations and sustainability practices within the industry. Course 4: Petroleum Refining Demystified Comprehend the processes involved in petroleum refining and its role in producing various fuel products. Analyze the challenges and technologies associated with cleaner and more efficient refining. Gain knowledge of safety measures and environmental considerations in petroleum refining. This Renewable Energy Complete Course Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments. Course 5: Online Course in Conservation Learn about the principles and methods of conservation biology and ecology. Understand the importance of biodiversity conservation and ecosystem management. Explore practical approaches to conserving natural resources and protecting endangered species. Course 6: Environment Management Develop skills in environmental management, including planning, monitoring, and assessment. Explore strategies for sustainable resource use and pollution control. Understand the regulatory frameworks and compliance requirements in environmental management. Course 7: Environmental Health Gain knowledge of environmental factors that impact public health. Learn about epidemiological methods for assessing and managing environmental health risks. Explore strategies for improving air and water quality and preventing environmental-related diseases. Course 8: Environmental Law 2021 Understand the legal frameworks and regulations governing environmental protection. Analyze case studies and recent developments in environmental law. Learn about compliance, enforcement, and the role of stakeholders in environmental legal issues. Course 9: Meteorology Acquire a foundational understanding of meteorology and weather forecasting. Learn about the science behind atmospheric phenomena and climate patterns. Explore the practical applications of meteorology in various industries. Course 10: Land Management Develop skills in land use planning, conservation, and sustainable land management. Learn about land tenure systems, property rights, and land-related policies. Explore techniques for land assessment, soil conservation, and land-use decision-making. Course 11: Diploma in Water Treatment Understand the principles of water treatment processes and their importance in ensuring clean and safe drinking water. Gain knowledge of various water treatment technologies and their applications in addressing water quality issues. Learn about the regulatory standards and quality control measures in water treatment. Course 12: Forestry Develop an understanding of forestry practices, including tree cultivation, maintenance, and sustainable harvesting. Explore the ecological and environmental aspects of forest ecosystems and biodiversity conservation. Learn about forestry management strategies and their role in sustainable resource utilization. Course 13: Agricultural Science Gain insights into the science of agriculture, including crop cultivation, soil management, and pest control. Understand the principles of sustainable farming and the use of technology in modern agriculture. Explore the challenges and opportunities in the agricultural sector. Course 14: Botany Study the fundamentals of botany, including plant anatomy, physiology, and taxonomy. Learn about plant diversity and the role of plants in ecosystems and human societies. Explore the applications of botany in fields such as agriculture, medicine, and conservation. Course 15: Wildlife Rescue and Rehabilitation Develop skills in rescuing and caring for injured or orphaned wildlife. Learn about wildlife rehabilitation techniques and ethical considerations. Understand the legal and regulatory aspects of wildlife rescue and rehabilitation. Course 16: Architectural Studies Explore the principles of architectural design, construction, and planning. Gain knowledge of architectural history and various architectural styles. Learn about sustainable architecture and its role in contemporary design. Course 17: Cleaning: Disinfection, Waste Management and Chemical Safety Understand the importance of cleaning, disinfection, and waste management in various settings. Learn about safe handling of chemicals and hazardous substances. Explore best practices for maintaining cleanliness and hygiene. Course 18: COSHH (Control of Substances Hazardous to Health) - Awareness Gain awareness of the COSHH regulations and their significance in workplace safety. Learn to identify hazardous substances and assess associated risks. Understand the measures and controls for safe handling of hazardous materials. Course 19: Spill Management Training Develop skills in responding to chemical spills and hazardous material incidents. Learn about containment and cleanup procedures for different types of spills. Understand the importance of risk assessment and prevention in spill management. Course 20: Horticulture & Organic Gardening Explore the principles of horticulture and organic gardening practices. Learn about plant propagation, soil health, and sustainable gardening techniques. Gain knowledge of organic pest control and environmentally friendly gardening. Course 21: Homesteading Diploma Gain knowledge and practical skills related to homesteading, including food production, self-sufficiency, and sustainable living. Learn about the principles of permaculture and how to create a self-sustaining homestead. Understand the basics of animal husbandry, crop cultivation, and homestead design. Course 22: Floristry Academy Diploma Develop expertise in floral design, arranging, and creating stunning flower arrangements. Learn about the different types of flowers, foliage, and their care and maintenance. Explore the art of floristry for various occasions, from weddings to special events. Course 23: Arboriculture Understand the science and practice of arboriculture, including tree care, maintenance, and preservation. Learn about tree biology, pruning techniques, and risk assessment in tree management. Gain knowledge of urban forestry and the importance of trees in urban environments. Course 24: Marine Biology Course - Online Diploma Explore marine ecosystems, biodiversity, and the role of marine organisms in aquatic environments. Learn about marine conservation, environmental threats, and the importance of protecting marine life. Gain insights into the field of marine biology and its relevance in scientific research. Course 25: Garden Design Develop skills in garden design, landscape planning, and creating outdoor spaces. Learn about garden styles, plant selection, and principles of garden aesthetics. Understand the practical aspects of garden construction and maintenance. Course 26: Escaping Consumerism Explore the concept of consumerism and its impact on individuals and society. Learn strategies for reducing consumption, living more sustainably, and embracing minimalism. Gain insights into the benefits of conscious consumer choices and alternative lifestyles. Certification After studying the complete Renewable Energy Complete Course training materials, you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of •8. CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Course 27: Administration of Emergency Medical Gases Acquire knowledge of emergency medical gases, their uses, and safe administration. Learn about the regulatory requirements and guidelines for handling medical gases in emergencies. Develop skills in responding to medical emergencies that require the use of medical gases. Course 28: Accredited level 3 Oceanography Diploma Explore the field of oceanography, including ocean dynamics, marine ecosystems, and climate science. Gain knowledge of oceanographic research methods and data analysis techniques. Understand the role of oceanography in addressing environmental challenges. Course 29: Hydrogen Sulphide Training: Safety and Awareness in Hazardous Environments Learn about the properties of hydrogen sulphide (H2S) and its hazards in industrial environments. Acquire skills in detecting, preventing, and responding to H2S emergencies. Understand safety protocols and equipment used in H2S-prone settings. Course 30: Public Realm Manager's Guide: Urban Planning and Management Explore urban planning principles, city management, and the role of public realm managers. Learn about urban design, public spaces, and strategies for enhancing the quality of urban life. Gain insights into sustainable urban development and effective public realm management. Course 31: Solar & Thermal Energy: Harnessing Renewable Power Sources Understand the principles of solar and thermal energy generation and their applications. Learn about renewable energy technologies, including solar panels and thermal systems. Explore the benefits of harnessing solar and thermal energy for sustainable power generation. Ambitious learners who want to strengthen their CV for their desired job should take advantage of the Renewable Energy Complete Course bundle! This bundle is also ideal for professionals looking for career advancement. Renewable Energy Researcher Clean Energy Advocate Solar Installation Manager Wind Farm Operations Manager Biomass Energy Developer Climate Change Analyst Sustainability Director Renewable Energy Auditor Biofuel Production Technician Solar Panel Inspector Green Supply Chain Manager Energy Policy Analyst Wind Turbine Designer Solar Project Coordinator Energy Storage Specialist Geothermal Plant Operator Hydropower Plant Manager Environmental Consultant Renewable Energy Consultant Clean Energy Project Manager Sustainable Architecture Designer Energy Efficiency Engineer Renewable Energy Planner Carbon Emissions Analyst Biomass Fuel Technician Solar Power Plant Manager Wind Energy Researcher Energy Management Analyst Renewable Energy Technician Bioenergy Analyst Solar Power Systems Designer Wind Turbine Maintenance Technician Hydropower Systems Engineer Environmental Scientist Sustainable Business Manager Green Energy Policy Advisor Wind Turbine Blade Technician Solar Energy Systems Engineer Sustainable Transportation Planner Renewable Energy Sales Representative Biomass Energy Systems Designer Carbon Offset Specialist Climate Risk Analyst Geothermal Energy Researcher Energy Efficiency Consultant Solar Energy Analyst Green Building Project Manager Wind Turbine Tower Technician Hydropower Plant Engineer Environmental Educator Clean Energy Investment Analyst Renewable Energy Project Developer Sustainable Product Designer Green Supply Chain Analyst Energy Policy Researcher Wind Energy Systems Engineer Solar Panel Manufacturing Technician Biofuel Production Engineer Energy Efficiency Auditor Hydropower Project Coordinator Environmental Impact Analyst Sustainable Agriculture Specialist Renewable Energy Market Analyst Biomass Power Plant Manager Solar Energy Systems Installer Wind Farm Construction Manager Green Energy Consultant Wind Turbine Systems Engineer Requirements Course 32: Sustainable Management of Renewable Energy Resources Develop expertise in the sustainable management of renewable energy sources. Learn about energy policy, renewable energy systems, and their environmental impact. Explore strategies for integrating renewable energy into existing energy grids and systems. Career path Renewable Energy Engineer Solar Power Technician Wind Turbine Technician Biomass Plant Operator Energy Analyst Energy Consultant Sustainability Coordinator Solar Sales Consultant Wind Energy Project Manager Green Building Consultant Energy Efficiency Specialist Geothermal Technician Hydropower Engineer Environmental Compliance Analyst

Step into the intriguing world of criminal intelligence with the 'Criminal Intelligence Researcher' course, a journey that blends criminology, intelligence, and justice. This course is a gateway to understanding the intricate web of criminal intelligence, beginning with foundational knowledge in this topic and crime intelligence analysis.  As you progress, the curriculum delves into the historical roots of analysis disciplines, fostering a deeper appreciation of the intelligence cycle and process. The inclusion of the UK's National Intelligence Model offers a real-world perspective, enhancing your understanding of the criminal justice system. Moreover, the course addresses the evolving field of crime science, emphasising the importance of pattern detection and analysis. You'll gain insights into critical thinking approaches, crime mapping, and strategic analysis, skills crucial for a criminal-intelligence analyst.  The journey culminates in exploring the realms of research, inference policing, and behavioural science, equipping you for diverse roles in criminal intelligence agencies and beyond. Learning Outcomes: Gain comprehensive knowledge of this field, including its application in crime analysis and justice. Understand the historical evolution and significance of this topic. Acquire skills in the intelligence cycle, crime mapping, and strategic analysis for practical application. Develop a critical thinking approach to analyse criminal patterns and statistics. Learn about the interplay of behavioural science in criminal intelligence and its role in modern policing strategies. Why buy this Criminal Intelligence Researcher Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the Criminal Intelligence Researcher you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Criminal Intelligence Researcher course for? Individuals aspiring to work in national criminal intelligence services. Graduates seeking criminal intelligence analyst jobs. Professionals in law enforcement seeking to enhance their analytical skills. Students interested in the intersection of artificial intelligence and criminal justice. Career switchers aiming to enter this field. Prerequisites This Criminal Intelligence Researcher was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Intelligence Analyst: £30,000 - £45,000 Per Annum Crime Data Analyst: £27,000 - £40,000 Per Annum Intelligence Researcher for National Services: £35,000 - £50,000 Per Annum Crime Pattern Analyst: £29,000 - £43,000 Per Annum Intelligence Officer in Criminal Justice: £31,000 - £46,000 Per Annum Forensic Behavioural Scientist: £32,000 - £48,000 Per Annum Course Curriculum Criminology, Intelligence and Criminal Justice Module 01: Criminal Intelligence and Crime Intelligence Analysis Module 01: Criminal Intelligence and Crime Intelligence Analysis 00:15:00 Module 02: A Historical Perspective on the Discipline of Analysis Module 02: A Historical Perspective on the Discipline of Analysis 00:15:00 Module 03: The Intelligence Cycle and Process Module 03: The Intelligence Cycle and Process 00:30:00 Module 04: Example of a National Intelligence Model: The United Kingdom Module 04: Example of a National Intelligence Model: The United Kingdom 00:15:00 Module 05: Introduction to Criminal Justice Module 05: Introduction to Criminal Justice 01:00:00 Crime Science, Pattern Detection and Analysis Module 06: Crime Science: Theories Principles and Intelligent Sources Module 06: Crime Science: Theories, Principles and Intelligent Sources 00:17:00 Module 07: Evaluation of Information Module 07: Evaluation of Information 00:15:00 Module 08: Introduction to the Analysis of Patterns, Statistics & Relationships Module 08: Introduction to the Analysis of Patterns, Statistics & Relationships 00:35:00 Thinking approach, Crime Mapping and Strategic Analysis Module 09: A Critical Thinking Approach to Analysis Module 09: A Critical Thinking Approach to Analysis 00:35:00 Module 10: Tactical Analysis with Crime Mapping and the GIS System Module 10: Tactical Analysis with Crime Mapping and the GIS System 00:20:00 Module 11: Strategic Analysis Variations Module 11: Strategic Analysis Variations 01:00:00 Module 12: Realising The Power of Analytics: Arming the Human Mind Module 12: Realizing The Power of Analytics: Arming the Human Mind 01:00:00 Research, Inference Policing and the Behavioural Science Module 13: Research Method and Statistics in Crime Analysis Module 13: Research Method and Statistics in Crime Analysis 00:20:00 Module 14: Inference Development and the Presentation of the Results Module 14: Inference Development and the Presentation of the Results 00:35:00 Module 15: Homeland Security and Counter Terrorism Module 15: Homeland Security and Counter Terrorism 01:30:00 Module 16: Models of Policing and Security Module 16: Models of Policing and Security 01:20:00 Module 17: Behavioural Sciences Module 17: Behavioural Sciences 00:10:00 Module 18: Career in CIA (Crime Intelligence Analyst) Module 18: Career in CIA (Crime Intelligence Analyst) 00:15:00 Additional Reading Materials Additional Reading Materials - Criminal Intelligence Researcher 00:00:00 Mock Exam Mock Exam - Criminal Intelligence Researcher 00:20:00 Final Exam Final Exam - Criminal Intelligence Researcher 00:20:00

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Aligned with the AIGP certification program, AI Governance Professional Training is for professionals tasked with implementing AI governance and risk management in their organizations. It provides baseline knowledge and strategies for responding to complex risks associated with the evolving AI landscape. This training meets the rapidly growing need for professionals who can develop, integrate and deploy trustworthy AI systems in line with emerging laws and policies. About This Course This training teaches critical artificial intelligence governance concepts that are also integral to the AIGP certification exam. While not purely a 'test prep' course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.   Module 1: Foundations of artificial intelligence Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context. Module 2: AI impacts on people and responsible AI principles Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI. Module 3: AI development life cycle Describes the AI development life cycle and the broad context in which AI risks are managed. Module 4: Implementing responsible AI governance and risk management Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems' potential societal benefits. Module 5: Implementing AI projects and systems Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment. Module 6: Current laws that apply to AI systems Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform. Module 7: Existing and emerging AI laws and standards Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed. Module 8: Ongoing AI issues and concerns Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues. Accreditation The associated exam is accredited by the IAPP under its ANSI Accreditation Who Should Attend? Any professionals tasked with developing AI governance and risk management in their operations, and anyone pursuing IAPP Artificial Intelligence Governance Professional certification. Prerequisites A general understanding of AI, Corporate Governance, and Business value would be of benefit to participants. Assessment As with all IAPP exams, the AIGP is a 90 question, multiple choice exam to be completed within 150 minutes. Exams are hosted by Pearsonvue and can be taken either remotely, or via any one of hundreds of exam venues globally. A passing score is achieved at 70% Our Guarantee We are an approved IAPP training provider Exam pass guarantee, or retrain until you do, for free What's Included? Participant Guide Study Guide Practice Exam Exam voucher Breakfast, lunch, coffees and snacks (Classroom courses only) Certification Logo

Take our part-time online “Conversion Course into Pharmaceutical Manufacturing“ NO Previous Industry Experience or Science Qualifications Required

Course Overview Julia is one of the highest performing programming languages. The Tutorials - The Julia Programming Language course is designed to train you in this valuable programing language. In this course, you will get equipped with the skills to code in Julia and add available skill sets to your resume. The Tutorials - The Julia Programming Language course will introduce you to the basic principles of Julia programming language. In this course, you will learn the steps to install Julia. You will get introduced to Julia variables, integers, sign function and more. The course will provide you with lectures based on Cher types and strings. You will start to understand all the functions of this programming language. The course will give you an extensive understanding of Julia Dict and type. By the end of the course, you will pick up all the valuable information and skills to use this language. Learn the ins and outs of Julia programming language from the Tutorials - The Julia Programming Language course. This course will increase your abilities and boost your employability in the relevant industry. Learning Outcomes Understand the process of installing Julia Familiarize yourself with Julia variables and functions Enrich your understanding of Cher types and strings Learn the details of conditional and non-conditional blocks Grasp the skills essential for Juila Dict operations Who is this course for? This Tutorials - The Julia Programming Language course is suitable for programmers, data scientists, or individuals who want to learn a new programming language. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path The Tutorials - The Julia Programming Language course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Programmer Data Scientist Introduction Learning Julia 00:01:00 Installing Julia 00:06:00 Installing Juno 00:04:00 Begin Dancing with Julia Julia Variables 00:05:00 Julia Integers and Floats 00:05:00 Julia Convert and Comparisons 00:03:00 Rounding Operations 00:05:00 Division Function 00:04:00 Sign Function and Power 00:05:00 Complex and Rational Numbers 00:05:00 Julia Chars and Strings Julia Char type 00:03:00 String Literals 00:02:00 Extract Char and String 00:02:00 Concatenate and Interpolate 00:03:00 isEqual and Comparisons 00:04:00 Find and OccursIn 00:05:00 Repeat and Regex 00:04:00 Julia Functions Julia Function Object 00:04:00 Function Return Type 00:06:00 Functions as Objects and Arguments 00:04:00 Operators as Functions 00:02:00 Anonymous Function 00:04:00 Function Arguments Tuples 00:05:00 Unpacking Tuples 00:02:00 Varargs 00:03:00 Optional Arguments 00:03:00 Keyword Arguments 00:03:00 Conditional and Non-Conditional Blocks Do Block 00:04:00 Compound Expression 00:02:00 If Statements 00:05:00 If Statement Return Value 00:02:00 Short Circuit Evaluation 00:03:00 Loops and Exceptions For Loop 00:02:00 Control and Nest For Loops 00:03:00 Exceptions 00:03:00 Julia Try and Catch 00:03:00 While Loop 00:02:00 Variable Scope 00:05:00 Arrays in Julia Arrays 00:04:00 Pop and Push 00:03:00 Multidimensional Arrays 00:03:00 Copying Arrays 00:02:00 Julia Dicts Dicts 00:02:00 Dict Operations 00:02:00 More Dict Operations 00:04:00 More Cool Dict Operations 00:03:00 One More Cool Dict Operation 00:04:00 Broadcasting 00:04:00 Julia Types Julia Types 00:01:00 Verify and Specify Types 00:03:00 More Verification and Specification 00:05:00 Julia Methods 00:02:00 Composite Types 00:05:00 Mutable Structs 00:02:00 Constructor Functions 00:04:00 Modules and Packages Julia Modules 00:02:00 Using Packages 00:04:00 User Defined Modules 00:05:00 Working with Text Files Reading Text Files 00:04:00 Writing To Text Files 00:03:00 Writing Collections To Files 00:02:00 Julia Date and Time Date And Time 00:03:00 Date Queries 00:02:00 Date Arithmetic 00:03:00 Meta Programming in Julia Meta Programming 00:02:00 Quoted Expression 00:04:00 Macros 00:02:00 REST APIs and MySQL Using Genie 00:04:00 Payloads and POST Requests 00:05:00 Julia and MySQL 00:08:00 DataFrames and Plots DataFrames 00:05:00 Plotting with Plots 00:02:00 Where to go from here 00:01:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Learn the essential knowledge and build solid skills in biotechnology with the Biotechnology course. This course will enrich your understanding of biology and present you with job opportunities in the field of business, healthcare, and other industries. Within no time, you will become competent and confident to establish a brilliant career. The Biotechnology course is divided into easy to follow bite-sized modules to help you understand every topic without difficulties. Here, you will learn the core principles and the history of biotechnology. The informative lectures will educate you on molecular and cellular biotechnology. In addition, you will receive the ability to identify the differences between biotechnology and molecular biology. This comprehensive course will also help you grasp the fundamentals of genetic engineering.  Through this Biotechnology course, you will understand the significance of biology in different industries, healthcare sectors and business sectors. At the end of this course, you will receive a valuable certificate, which you'll elevate your resume and boost your employability in the relevant sector. Enrol today! Please note: Our Biotechnology course only gives you theoretical knowledge to excel in this field. This course doesn't entitle you to practise as a professional in this specific field. Learning Objectives Get introduced to the basics of biotechnology Learn about the history of biotechnology Enrich your knowledge of molecular and cellular biology Understand the difference between biotechnology and molecular biology Grasp the principles of genetic engineering Know the fundamental of industrial biotechnology Understand the role of biotechnology in the health and business sector Who is this Course for? This Biotechnology course is ideal for aspiring biotechnologists who wish to gain the relevant skills and knowledge to fast track their careers. It is for those who have little or no knowledge of the principles of biotechnology or those who are new to the field and want to test their skills and knowledge. There are no entry requirements for this course; however, an eye for detail and a creative mind is essential. Entry Requirement Anyone interested in learning more about this subject should take this Biotechnology course. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £4.99 and the hard copy for £9.99. Also, you can order both PDF and hardcopy certificates for £12.99. Career path On successful completion of the Biotechnology course, learners can progress to a more advanced program from our course list. Career opportunities in this field include freelancing or working in-house, within a range of professional settings, with the opportunity to earn a high salary. Related professions in this industry include: Biomedical Engineer Biochemist Clinical Technician Microbiologist Process Development Scientist Biomanufacturing Specialist Business Development Manager Medical Lab Technologist Microbiologist Clinical Support Specialist Course Curriculum Module 1 - Introduction to Biotechnology Introduction to Biotechnology 00:19:00 Module 2- Biotechnology in the Realm of History Biotechnology in the Realm of History 00:27:00 Module 3- Molecular and Cellular Biology Molecular and Cellular Biology 00:27:00 Module 4 - Biotechnology Versus Molecular Biology Biotechnology Versus Molecular Biology 00:11:00 Module 5- Genetic Engineering Genetic Engineering 00:16:00 Module 6- Biotechnology in Health Sector Biotechnology in Health Sector 00:11:00 Module 7- Industrial Biotechnology Industrial Biotechnology 00:14:00 Module 8- Biotechnology in a Business Perspective Biotechnology in a Business Perspective 00:13:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Learning Outcomes Get an introduction to Python programming Know how to do conditional branching with Python Deepen your knowledge of importing external/internal libraries in Python Learn about project rock, paper and scissors as well as strings operation, time and date in Python Acquire more knowledge about data storage structures, tuples, lists and dictionary Enhance your understanding of import tricks, import operating systems and platforms and exception handling in Python Learn how to instal Packages and Scheduling in Python Description Python is a highly multi-purposeful still easy-to-understand programming language, which is why it is more adaptable all over the world. Whether to make a web application in data science, software engineering, mobile app development, or artificial intelligence - every industry uses Python to accomplish its work. Therefore, if you are planning to pursue a career in these sectors, develop your Python skills with the Diploma In Python Programming course. We made this course with an aim of enhancing your programming language skills in Python and making you job ready. Therefore, this course includes some easy-to-digest modules on topics such as - conditional branching with Python, writing user functions in Python, file handling, reading and writing using Python and many more. Moreover, we will introduce you to the procedure of data storage structures, tuples, lists and dictionaries through Python. Further topics will be discussed in the modules for which you need to enrol in our comprehensive course. So, join this course now to acquire the exclusive knowledge of Python and a CPD certificate of achievement after completing this course. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post. Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career path After finishing this course you will get the expertise to aim for a career in the following positions: Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst Course Content Unit 01: Introduction to Python Programming Module 01: Course Introduction 00:02:00 Unit 02: Getting Started with Python Module 01: Software Installation 00:02:00 Module 02: Hello World Program 00:06:00 Module 03: Input and Output 00:07:00 Module 04: Calculating Average of 5 Numbers 00:03:00 Unit 03: Conditional Branching with Python Module 01: If Loop In Python 00:06:00 Module 02: Program Using If Else part 1 00:03:00 Module 03: Program Using If Else part 2 00:08:00 Module 04: Program for Calculator 00:02:00 Module 05: Program Using For Loop 00:08:00 Module 06: For Table 00:05:00 Module 07: For loop and Mathematical Operator in Python 00:04:00 Module 08: Factorial of Number Using Python 00:06:00 Module 09: Program Using While 00:05:00 Module 10: While Loop Example 00:07:00 Module 11: Tasks for Practice 00:02:00 Unit 04: Importing external/internal library in python Module 01: Importing Library in Python 00:07:00 Unit 05: Project Rock Paper and Scissors Module 01: Rock Paper and Scissor Game 00:06:00 Unit 06: Strings Operation in Python Module 01: Program Using String part 1 00:05:00 Module 02: Program using String 2 00:06:00 Module 03: Program Using String 3 00:06:00 Module 04: Program Using String part 4 00:03:00 Unit 07: Date and time in Python Module 01: Use of Date and Time part 1 00:05:00 Module 02: Use of Date and Time part 2 00:05:00 Unit 08: File Handling, read and write using Python Module 01: File Handling Part 1 00:08:00 Module 02: File Handling Part 2 00:07:00 Unit 09: Data Storage Structures, Tuple, List and Dictionary Module 01: Tuple in Python Part 1 00:10:00 Module 02: Tuple in Python Part 2 00:07:00 Module 03: Using Lists part 1 00:07:00 Module 04: Using List part 2 00:12:00 Module 05: Using Lists part 3 mm 00:06:00 Module 06: Using Lists part 4 00:08:00 Module 07: Using Lists part 5 00:02:00 Module 08: Use of Dictionary Part 1 00:04:00 Module 09: Use of Dictionary Part 2 00:05:00 Module 10: Use of Dictionary Part 3 00:08:00 Module 11: Use of Dictionary Part 4 00:07:00 Unit 10: Writing user functions in Python Module 01: Function in Python Part 1 00:06:00 Module 02: Function in Python Part 2 00:05:00 Module 03: Function in Python Part 3 00:04:00 Module 04: Function in Python Part 4 00:07:00 Module 05: Function in Python Part 5 00:08:00 Unit 11: Sending mail Module 01: Send Email 00:09:00 Unit 12: Import Tricks in Python Module 01: Import Study part 1 00:07:00 Module 02: Import Study part 2 00:03:00 Unit 13: Import Operating System and Platform Module 01: Importing OS 00:06:00 Module 02: Import Platform 00:05:00 Unit 14: Exceptions handling in python Module 01: Exception in Python part 1 00:11:00 Module 02: Exception in Python part 2 00:07:00 Module 03: Exception in Python part 3 00:05:00 Unit 15: Installing Packages and Scheduling In Python Module 01: Installing Packages using built in package manager 00:08:00 Module 02: Scheduler in Python 00:05:00 Unit 16: Data Base In Python using sqlite Module 01: Data Base 1 00:08:00 Module 02: Data Base 2 00:09:00 Module 03: Data Base 3 00:08:00 Module 04: Data base 4 00:07:00 Module 05: Data Base 5 00:06:00 Unit 17: Running Program from Command Prompt and jupyter Notebook Module 01: IDE_1 00:05:00 Module 02: IDE_2 00:07:00 Unit 18: Conclusion Module 01: Conclusion 00:02:00 Resources Resources - Diploma in Python Programming 00:00:00 Recommended Materials Workbook - Diploma in Python Programming 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00

Scala is doubtless one of the most in-demand skills for data scientists and data engineers. This competitive course will teach you the essential concepts and methodologies of Scala with a lot of practical implementations.

Embark on a transformative journey into the realm of programming with our Intermediate Python Coding course. Picture yourself delving deeper into the world of Python, a language known for its versatility and efficiency. This course begins with a refresher introduction, setting a solid foundation before advancing to more complex concepts. It's designed not just to teach but to immerse you in the intricacies of Python. From understanding the fundamentals of classes and methods to unraveling the complexities of Object-Oriented Programming (OOP), each section is a step towards mastering this powerful programming language. Whether you're looking to enhance your coding skills for professional growth or personal satisfaction, this course bridges the gap between basic understanding and advanced proficiency. As you progress, you'll explore the sophisticated elements of Python, including inheritance, polymorphism, encapsulation, and abstraction. These concepts are not just taught theoretically; you'll see them come to life through practical applications, especially in the creation of Python games. This hands-on approach ensures that you're not just learning concepts but also applying them in real-world scenarios. The course also delves into Python's extensive libraries as you learn about modules, packages, and data handling with Pandas. Completing the course with error and exception handling, you emerge not just as someone who can code but as a problem-solver who can navigate through challenges and create efficient, elegant solutions. Learning Outcomes Gain a deeper understanding of Python classes, methods, and OOP principles. Develop skills in implementing inheritance, polymorphism, encapsulation, and abstraction in Python. Create interactive Python games and applications to apply coding skills practically. Learn to manage and utilise Python modules, packages, and the Pandas library. Master error and exception handling in Python for robust coding. Why choose this Intermediate Python Coding course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Intermediate Python Coding course for? Programmers looking to advance from basic to intermediate Python skills. Computer science students seeking a deeper understanding of Python. Software developers aiming to enhance their proficiency in Python. Data analysts and scientists interested in leveraging Python's capabilities. Hobbyists and tech enthusiasts keen on developing Python applications. Career path Software Developer: £30,000 - £60,000 Data Analyst: £25,000 - £50,000 Python Developer: £28,000 - £55,000 Machine Learning Engineer: £32,000 - £70,000 Data Scientist: £35,000 - £75,000 Back-end Developer: £27,000 - £53,000 Prerequisites This Beginner to Intermediate Python Coding does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Beginner to Intermediate Python Coding was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Course Introduction 00:02:00 Course Curriculum 00:05:00 How to get Pre-requisites 00:02:00 Getting Started on Windows, Linux or Mac 00:01:00 How to ask Great Questions 00:02:00 Section 02: Class Introduction to Class 00:07:00 Create a Class 00:09:00 Calling a Class Object 00:08:00 Class Parameters - Objects 00:05:00 Access Modifiers(theory) 00:10:00 Summary 00:02:00 Section 03: Methods Introduction to methods 00:06:00 Create a method 00:07:00 Method with parameters 00:12:00 Method default parameter 00:06:00 Multiple parameters. 00:05:00 Method return keyword. 00:04:00 Method Overloading. 00:05:00 Summary 00:02:00 Section 04: OOPs Object-Oriented Programming Introduction to OOPs 00:05:00 Classes and Objects 00:08:00 Class Constructors 00:07:00 Assessment Test1 00:01:00 Solution for Assessment Test1 00:03:00 Summary 00:01:00 Section 05: Inheritance and Polymorphism Introduction 00:04:00 Inheritance 00:13:00 Getter and Setter Methods 00:12:00 Polymorphism 00:13:00 Assessment Test2 00:03:00 Solution for Assessment Test2 00:03:00 Summary 00:01:00 Section 06: Encapsulation and Abstraction Introduction 00:03:00 Access Modifiers (public, protected, private) 00:21:00 Encapsulation 00:07:00 Abstraction 00:07:00 Summary 00:02:00 Section 07: Python Games for Intermediate Introduction 00:01:00 Dice Game 00:06:00 Card and Deck Game Playing 00:07:00 Summary 00:01:00 Section 08: Modules and Packages Introduction 00:01:00 PIP command installations 00:12:00 Modules 00:12:00 Naming Module 00:03:00 Built-in Modules 00:03:00 Packages 00:08:00 List Packages 00:03:00 Summary 00:02:00 Section 09: Working Files with Pandas Introduction 00:02:00 Reading CSV files 00:11:00 Writing CSV files 00:04:00 Summary 00:01:00 Section 10: Error and ExceptionHandling Introduction 00:01:00 Errors - Types of Errors 00:08:00 Try - ExceptExceptions Handling 00:07:00 Creating User-Defined Message 00:05:00 Try-Except-FinallyBlocks 00:07:00 Summary 00:02:00