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Numerical analysis lessons in Berrechid

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Olesia - Paris, France£22
£22Computer training, Database, Data science, Data Analytics, BI, Big Data
Trusted teacher: I offer courses in data development / database / machine learning / data science (python): I also offer the possibility of helping you with the realization of your academic projects. We support you in the Data development of your business. -1- Databases & Data warehouses (AWS / Google Cloud / Azure Cloud) -2- Machine Learning -3- Deep Learning (tensorflow, pytorch, RNN, CNN, LSTM) -4- Data Processing -5- Machine Learning design and deployment (docker, ...) -6- Data Pipelines -7- Google Sheets with Realtime Pipelines, Macro (VBA) & Database Connection -8- Online dashboards on browsers or on your Excel, Google Sheets (Python, R, Power BI, Tableau, Kibana, etc.) - Our Tech Stack - - Databases: AWS DynamoDB, Amazon Redshift, PostgreSQL, MySQL, multi-cube DBs (EPM / BI platform) - Languages: Python, Spark (Scala, Python, Java), JavaScript, CSS, HTML - Development environment: JSON, SQL, NoSQL, Bash Shell Scripting, Jupyter Notebook, Anaconda, REST API, VSCode, DBeaver, Google services, Platform as a Service (PAAS), Apache Airflow, Serverless Computing, SublimeText - Clouds: Amazon Web Services, Azure Databricks, Google GCP (Google Firebase) - Data Lake AWS / Databricks: EC2 (Linux), IAM, Amazon MWAA (Managed Workflows for Apache Airflow), Lambda, S3, DynamoDB, RedShift; Kibana, Azure Databricks, CloudFormation - Web crawling / Scraping: Python Scrapy - Data streaming: Airflow, Kafka - Data visualization / ETL: Python, Kibana, Tableau, Power BI & DAX, Excel Power Query (and lang.M) - Continuous integration workflows (CI / CD): Docker / Google cloud / Kubernetes; Amazon ECS) - Containerized applications: Docker (Docker container, Docker-compose) - Virtualization technologies: VirtualBox, Vmware - Agile tools: Version control (Git / GitLab), tickets (JIRA), Bitbukets, Trello, Wiki (Confluence), Jetbrains - OS: Linux, Windows
Numerical analysis · Information technology · Database
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William - Accra, Ghana£12
£12Fundamentals of SPSS for Biologists: A step by step approach to doing more with SPSS
Trusted teacher: 🔰 SPSS is one of the leading statistical tools used by researchers, data scientists, and students worldwide. 🔰 Whether you are exploring trends in biological research, conducting surveys, or analyzing experimental data, SPSS empowers you to transform raw data into actionable insights. 🔰 In this comprehensive course, you will learn the fundamentals of SPSS in a simple, step-by-step manner, tailored for individuals from any background. 🔰 By the end, you will be equipped with the essential skills to analyze, interpret, and present data confidently, making this course an invaluable tool for your research or professional journey. COURSE OUTLINE ✳️ Module 1: Introduction to SPSS ◘ Lesson 1.1: What is SPSS and Why Should Biologists Use It? • Overview of SPSS • Key features and benefits for biological research ◘ Lesson 1.2: Installing and Navigating SPSS • Installation guide • Understanding the SPSS interface • Data entry basics: How to input data manually ◘ Lesson 1.3: Data Types and Variables • Understanding variable types (Nominal, Ordinal, Scale) • Setting up variables in SPSS ✳️ Module 2: Data Management and Organization ◘ Lesson 2.1: Importing and Exporting Data • Importing Excel, CSV, and other formats into SPSS • Exporting data and results from SPSS ◘ Lesson 2.2: Data Cleaning and Preparation • Handling missing values • Sorting and filtering data • Recode and compute variables ◘ Lesson 2.3: Data Transformation for Biological Analysis • Creating new variables based on existing data • Using conditional statements ✳️ Module 3: Descriptive Statistics ◘ Lesson 3.1: Basic Descriptive Statistics • Mean, Median, Mode, Range, and Standard Deviation • Using SPSS to calculate and interpret descriptive statistics ◘ Lesson 3.2: Visualizing Data • Creating histograms, bar charts, and pie charts • Using boxplots and scatterplots for biological data ✳️ Module 4: Hypothesis Testing in SPSS ◘ Lesson 4.1: Introduction to Hypothesis Testing • Understanding p-values, significance, and confidence intervals ◘ Lesson 4.2: T-Tests and ANOVA • Independent and Paired Sample T-Tests • One-way and Two-way ANOVA ◘ Lesson 4.3: Non-Parametric Tests • Mann-Whitney U Test, Kruskal-Wallis Test • When to use non-parametric tests in biology ✳️ Module 5: Correlation and Regression Analysis ◘ Lesson 5.1: Correlation Analysis • Pearson’s and Spearman’s correlation • Interpreting correlation coefficients in biological research ◘ Lesson 5.2: Linear Regression • Simple linear regression • Multiple linear regression: When and how to use it • Assumptions of linear regression ◘ Lesson 5.3: Logistic Regression • Understanding binary outcomes • Conducting and interpreting logistic regression ✳️ Module 6: Advanced Statistical Techniques ◘ Lesson 6.1: Factor Analysis • Overview and applications in biology • Conducting factor analysis in SPSS ◘ Lesson 6.2: Cluster Analysis • Hierarchical and K-means clustering • Applications in biological data sets ◘ Lesson 6.3: Multivariate Analysis of Variance (MANOVA) • When to use MANOVA in biological research • Conducting and interpreting MANOVA ✳️ Module 7: Reporting and Interpreting Results ◘ Lesson 7.1: Generating and Interpreting Output • Understanding SPSS output tables and charts • Reporting statistical findings in biological research ◘ Lesson 7.2: Writing a Statistical Report • Structuring a scientific report with statistical results • Communicating complex data simply and effectively ✳️ Module 8: SPSS for Biological Research Projects ◘ Lesson 8.1: Designing a Research Project Using SPSS • Setting research objectives and data collection strategies • Using SPSS for hypothesis testing and analysis ◘ Lesson 8.2: Case Studies in Biology • Real-world biological examples using SPSS (e.g., population genetics, ecology, microbiology) • Hands-on project using SPSS to analyze biological data ✳️ Final Project ◘ Lesson 9.1: Capstone Project • Students will analyze a biological dataset using the techniques learned in the course • Submission of a final report including data analysis, results, and conclusions
Database · Biology · Numerical analysis
Stephen - Germany£21
£21Maths for High School Students. Best suited for ages 13-17!
I am Stephen, now living in Schwaig bei Nuernberg, Bayern, Germany. Prior to moving here, I lived all my life in New Zealand. With 20 years of experience of successful classroom teaching, including 9 years as HoD of an Anglican Girls School in rural New Zealand, I can help students of all abilities and at all levels of high school. I am happy to start with ages 12-16, as these years are where the foundation for successful maths is built. I work hard to build a good rapport with students. I ask questions to understand where students are up to and to diagnose their strengths and weaknesses. I expect students to ask me as many questions as they need to grasp a concept, to practice it, to apply it, and to master it. I am innovative and flexible and bring plenty of ways to make maths interesting. I know many students are not big fans of maths, but I help them to believe they can still be good at maths and can learn with confidence. I am a supportive and encouraging teacher, and I have helped many students to improve and to succeed in maths. I have given many one-on-one tutorials at lunchtimes and after school, so I am very comfortable with individual tuition. I enjoy teaching, and I really want students to enjoy learning. This often shows up in increased motivation and a willingness to tackle topics students might have thought were beyond them. Together we can enjoy learning. I love helping students to 'get maths', and I will stick with them until they do. I hope you will consider me as your personal tutor.
Algebra · Geometry · Numerical analysis
Zahra - France£11
£11Math tutoring, Complete program-CRPE-All levels-Tutoring
Trusted teacher: Hello, my name is Zahra, I am a doctoral researcher in applied mathematics with extensive experience. I offer personalized lessons in mathematics, I have worked with students of all levels and with very different objectives, My journey : First of all, I obtained a Bac science maths with mention Assez Bien, After I then engaged in math studies and then I obtained a LICENSE in applied mathematics then I also obtained the MASTER in mathematics applied and now I am in second year DOCTORATE option numerical analysis. My experience I am a full-time private teacher. During these years I worked for several sites specializing in tutoring which allowed me to help students from all walks of life and from the (6th to the final) or even students preparing for the CRPE. I was thus able to occasionally help or follow several hundred students over the long term, some of whom were in school. I know perfectly well how to use the various tools available and know how to use them to make the courses dynamic, interesting and effective. My teaching method the lessons will guide them according to your needs always focused on improving your performance, as each student is different I will always adapt to them. My method is as follows: - Course and methodology points after analysis of the student's difficulties. - application exercises - intensive preparation of controls If you want more information or better explain your case do not hesitate to send me a message
Math · Algebra · Numerical analysis
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Numerical Analysis in Berrechid