1143 Data Analysis courses in Manchester delivered Online

In this course, you will learn how to perform data cleaning and data preparation with KNIME and without coding. You should be familiar with KNIME as no basics are covered in this course. Basic knowledge of machine learning is certainly helpful for the later lectures in this course.

Throughout this course, you will learn everything you need to know about linear and non-linear regression, regression modeling, and Stata. By the end of this course, you will be able to understand and be confident in interpreting complex types of data using Stata.

Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - Identifying Basic Concepts of Data Schemas Identify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization 2 - Understanding Different Data Systems Describe Types of Data Processing and Storage Systems Explain How Data Changes 3 - Understanding Types and Characteristics of Data Understand Types of Data Break Down the Field Data Types 4 - Comparing and Contrasting Different Data Structures, Formats, and Markup Languages Differentiate between Structured Data and Unstructured Data Recognize Different File Formats Understand the Different Code Languages Used for Data 5 - Explaining Data Integration and Collection Methods Understand the Processes of Extracting, Transforming, and Loading Data Explain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data Use and Collect Survey Data 6 - Identifying Common Reasons for Cleansing and Profiling Data Learn to Profile Data Address Redundant, Duplicated, and Unnecessary Data Work with Missing Value Address Invalid Data Convert Data to Meet Specifications 7 - Executing Different Data Manipulation Techniques Manipulate Field Data and Create Variables Transpose and Append Data Query Data 8 - Explaining Common Techniques for Data Manipulation and Optimization Use Functions to Manipulate Data Use Common Techniques for Query Optimization 9 - Applying Descriptive Statistical Methods Use Measures of Central Tendency Use Measures of Dispersion Use Frequency and Percentages 10 - Describing Key Analysis Techniques Get Started with Analysis Recognize Types of Analysis 11 - Understanding the Use of Different Statistical Methods Understand the Importance of Statistical Tests Break Down the Hypothesis Test Understand Tests and Methods to Determine Relationships Between Variables 12 - Using the Appropriate Type of Visualization Use Basic Visuals Build Advanced Visuals Build Maps with Geographical Data Use Visuals to Tell a Story 13 - Expressing Business Requirements in a Report Format Consider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting Describe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards Understand Ways to Sort and Filter Data 14 - Designing Components for Reports and Dashboards Design Elements for Reports and Dashboards Utilize Standard Elements Creating a Narrative and Other Written Elements Understand Deployment Considerations 15 - Understand Deployment Considerations Understand How Updates and Timing Affect Reporting Differentiate Between Types of Reports 16 - Summarizing the Importance of Data Governance Define Data Governance Understand Access Requirements and Policies Understand Security Requirements Understand Entity Relationship Requirements 17 - Applying Quality Control to Data Describe Characteristics, Rules, and Metrics of Data Quality Identify Reasons to Quality Check Data and Methods of Data Validation 18 - Explaining Master Data Management Concepts Explain the Basics of Master Data Management Describe Master Data Management Processes Additional course details: Nexus Humans CompTIA Data Plus (DA0-001) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the CompTIA Data Plus (DA0-001) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Learn to build an HR Dashboard using Excel with our comprehensive course. From data introduction to designing index and tabs, analyze employee data effectively using pivot tables and charts. Ideal for HR professionals and analysts looking to create insightful dashboards for HR metrics and analysis.

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Dive into the intricate world of deep learning with this sharply focused course on heuristic techniques using R. This programme is designed for learners keen to understand how heuristics shape machine learning models, particularly in deep neural networks. Whether you're brushing up on your algorithmic intuition or delving deeper into optimisation patterns, this course delivers a solid framework rooted in logic, not lingo. With R as your analytical companion, you'll explore neural computation, gradient-based strategies, backpropagation nuances, and heuristic-inspired adjustments that enhance model efficiency. This isn't about flashy tools or inflated claims — it's about getting your mind around how deep learning truly works, one clever calculation at a time. No fluff, no filler — just clear insights and well-paced learning to support your journey through the matrix of machine intelligence. Learning Outcomes: Develop an understanding of experimental design and how it applies to heuristics. Learn how to apply heuristics to real-world problems in the agriculture, cryptocurrency, energy, and financial markets sectors. Understand how to use R programming language for deep learning heuristics. Develop skills in analyzing data sets and creating predictive models. Learn how to implement different heuristics algorithms in R programming. The Essential Training on Deep Learning Heuristic using R is designed to provide students with a comprehensive understanding of heuristics and how they can be applied to various real-world problems. The course covers experimental design, data analysis, and predictive modelling using R programming language. Students will learn about different heuristics algorithms and how to implement them in R to solve complex problems in the agriculture, cryptocurrency, energy, and financial markets sectors. Throughout the course, students will work on various projects that will help them develop practical skills in analyzing data sets and creating predictive models. They will learn how to design experiments, collect and analyse data, and create models that can be used to make predictions. By the end of the course, students will have a strong understanding of heuristics, and deep learning, and how to apply them to solve real-world problems. Essential Training on Deep Learning Heuristic using R Course Curriculum Section 01: Experimental Design - Heuristics Project 1-Agriculture Section 02: Experimental Design - Heuristics Project 2-Cryptocurrencies Section 03: Experimental Design: Heuristics Project 3-Energy Sector Section 04: Experimental Design: Heuristics Project 4-Financial Markets How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data scientists who want to learn how to apply deep learning heuristics to solve real-world problems. Programmers who want to learn R programming language for data analysis and predictive modeling. Professionals in the agriculture, cryptocurrency, energy, and financial markets sectors who want to apply heuristics to solve complex problems. Students who want to learn about deep learning heuristics and how they can be applied to real-world problems. Anyone interested in developing practical skills in data analysis and predictive modelling using R programming language. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Deep Learning Engineer: £30,000 - £90,000 AI Researcher: £40,000 - £120,000 Data Scientist: £35,000 - £90,000 Machine Learning Engineer: £40,000 - £100,000 AI Architect: £50,000 - £150,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. 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 completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions.

Unlock the power of data with our “Data Science and Data Analytics” course. From setting up your data science environment to mastering essential packages like NumPy, Pandas, and Matplotlib, this program empowers you to analyze, visualize, and derive actionable insights from data.

Explore the diverse landscape of People Analytics, delving into data sources, cleaning methodologies, and statistical measures. Embrace the importance of ethical considerations and real-world applications, culminating in a comprehensive understanding of this evolving field. This course equips you with the skills to navigate People Analytics effectively. Learn to identify and leverage various data sources, apply cutting-edge data analysis techniques, and address challenges associated with ethical considerations, biases, and small sample sizes. Bridge theory with practicality through real-world examples and case studies. After the successful completion of this course, you will be able to: Identify the Different Data types and Sources used in People Analytics. Explain the Importance of Data Cleaning and Preparation in People Analytics. Apply Data Analysis Techniques, and Interpret Statistical Measures Used in People Analytics. Recognise the Challenges Associated with Collecting and Analysing People-Related Data and Formulate Strategies for Addressing the Challenges. Understand the Ethical Considerations Associated with Collecting and Analysing People-Related Data Such as Informed Consent and Confidentiality This course equips you with the essential skills to gather, clean, and analyze people-related data, transforming it into actionable insights that empower better HR decisions and ultimately, business success. You'll gain hands-on experience with data visualization tools, statistical analysis techniques, and practical strategies for tackling common challenges. By delving into real-world case studies and ethical considerations, you'll graduate with the confidence and expertise to champion data-driven HR initiatives that unlock the full potential of your workforce. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Data Collection and Analysis for People Analytics Self-paced pre-recorded learning content on this topic. Data Collection and Analysis for People Analytics Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be an added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone who is eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. People Analytics Specialist HR Data Analyst Workforce Insights Manager Employee Experience Analyst HR Research Consultant Talent Analytics Strategist Data-driven HR Manager Organizational Behavior Analyst Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

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