Intermediate Data Analytics Online Training

@OutsourceMan

Hi, CnEL India can support the development and delivery of your intermediate data analytics training, covering Excel, Python analytics and introductory machine learning. Our methodology: * Assess the students’ existing knowledge and define clear intermediate-level outcomes. * Structure sessions progressively from Excel analytics to Python and ML. * Cover PivotTables, lookup functions, Power Query and practical Excel dashboards. * Use real datasets to demonstrate cleaning, transformation and analysis workflows. * Teach Python with pandas for data wrangling and matplotlib/seaborn for visualization. * Introduce scikit-learn through a practical supervised-learning example. * Use live screen sharing and coding demonstrations with troubleshooting during sessions. * Provide concise slides, practice datasets, notebooks and Excel exercises after each class. * Assign short exercises to reinforce each topic. * Build a practical capstone project combining data preparation, visualization and a basic ML model. * Review exercises and provide structured feedback on learning outcomes. * Keep materials organized for students to revisit after the programme. * Adjust pacing based on student progress and questions. We would first finalize the syllabus, session structure and datasets, then deliver the programme progressively with practical exercises and a final capstone. Training experience/materials: [verified details].

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Python, and similar tools. I have worked with pytorch, and tensorflow to develop DL models, .I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@mayankinnovative

Bridging classic Excel analysis with intermediate Python requires structured, hands-on pedagogy that connects business spreadsheets to programmatic data science. I will guide your cohort from advanced Excel workflows into Python data wrangling, visualization, and baseline machine learning with measurable outcomes. my approach: I will deliver live, interactive sessions beginning with Excel lookups, Power Query automation, and dynamic KPI dashboards, establishing solid analytical foundations. We will then transition to Python using Jupyter notebooks, translating spreadsheet intuition into pandas data manipulation, matplotlib/seaborn statistical plotting, and scikit-learn predictive workflows. Each class will include curated practice datasets, exercise notebooks, and a real-world capstone project to validate skill acquisition. A few questions to align: 1. What is the intended cohort size and preferred session frequency? 2. Are students using local Python environments or cloud-based setups like Google Colab? I am ready to deliver an engaging, practical curriculum that elevates your students' analytical confidence.

@DeMit19

=====> Hi there, <===== I'd deliver a practical live training programme that moves your students from intermediate Excel into hands-on Python analytics, with every session focused on real datasets, live problem-solving and measurable outcomes. The course would cover Excel pivot tables, XLOOKUP/INDEX-MATCH, Power Query and basic dashboards, then transition into Python with pandas for cleaning/reshaping, matplotlib/seaborn for visualisation, and scikit-learn for a first supervised ML model. Each class would include live screen-sharing/coding, concise slides, practice datasets, notebooks/Excel files, short exercises and troubleshooting. I’d finish with a mini capstone combining data preparation, visualisation and basic predictive modelling. Question: How many live sessions and students are you planning for the cohort? Best regards, Dejan

@bojans9

Hello, I can structure and deliver this intermediate data analytics training around practical exercises rather than theory, taking students from advanced Excel workflows into hands-on Python analytics. I will cover: * Excel PivotTables, advanced lookups and data cleaning * Power Query and practical dashboard creation * Python fundamentals for analytics * pandas data cleaning, reshaping and aggregation * matplotlib/seaborn visualizations * scikit-learn fundamentals and a first supervised model * Real-time coding, troubleshooting and Q&A * Practice datasets, notebooks and Excel exercises * Short assignments after each module * Capstone mini-project with clear learning outcomes I would structure each session as explanation -> live demonstration -> guided exercise -> student practice -> review, so the cohort continuously applies what they learn. Rate: INR 1,000/hour Timeline: 2-3 weeks depending on session frequency Start: Immediately I can provide sample training materials during the discussion and tailor the syllabus to the students' current Excel and Python level. Best regards, Bojan

@indreshpnk

Hello, I understand you need an instructor to take students from basic data analysis to intermediate Excel and Python analytics, including practical data cleaning, visualization, and introductory machine learning. The goal is to make every session hands-on, with exercises and a capstone project that demonstrate real learning outcomes. Here’s what I can provide: Live Excel sessions covering PivotTables, lookup functions, Power Query, dashboards, and practical data-analysis workflows. Hands-on Python training with pandas for cleaning/reshaping, matplotlib/seaborn for visualization, and scikit-learn for introductory supervised ML. Concise slides, practice datasets, notebooks/Excel files, exercises, and a structured mini-project after the course. I bring over 4+ years of software development experience with Python, SQL, data handling, APIs, and full-stack applications. I’m comfortable explaining technical concepts step-by-step and connecting theory with practical implementation, including DSA and machine-learning fundamentals. Just to clarify a few things: How many sessions and total teaching hours are planned? What is the current skill level and expected cohort size? Please come to the chat box to discuss more about your project. Best regards Indresh Kushwaha

@ronakkataria1

Intermediate is the hardest cohort to teach, because five different levels turn up in one room. So session one is a short diagnostic notebook rather than a lecture: a few Excel tasks and a few pandas tasks that tell me who is where. It takes twenty minutes and it changes the pace of everything after it. The place these cohorts actually split is the Excel to Python crossing. In a spreadsheet you see the cell you changed. In pandas the same edit can hit a copy rather than the frame, so nothing errors and the number is quietly wrong later. I teach loc and iloc and why chained assignment bites, early, because students who miss it spend the rest of the course debugging silence. For the scikit-learn section at this level, one honest baseline beats a tour of algorithms: a train and test split, one model, and a hard look at leakage, because a student whose accuracy is 0.99 has almost always leaked the target. Each session ships with the notebook, the dataset and one short exercise, and the capstone is small enough to finish and specific enough to mark. How many students in the cohort, and how many hours per week do you have them for? Ronak

@kamanil

Hi, I can conduct this intermediate data analytics training with a practical mix of Excel and Python, focused on real classroom delivery and hands-on exercises. I have strong experience in Python, Excel, data analysis, data visualization, and machine learning basics. My approach will be: 1. Excel module: pivot tables, lookup functions, Power Query, and simple dashboards. 2. Python module: pandas for cleaning and reshaping, matplotlib or seaborn for visuals. 3. ML basics: introduction to scikit-learn with one supervised model. 4. Training support: live screen-sharing sessions, practice datasets, short exercises, and capstone mini-project. 5. After each class: slide deck, notebook or Excel file, and notes for revision. For timeline, I can structure this in a 2-week plan depending on session count and cohort pace. If you want, I can also share a sample outline for the first 3 sessions before we start. Best, Anil K

@abhilashr53

I can deliver 'Intermediate Data Analytics Online Training' end to end — clean architecture, tests, and deployment. I'll start with a short plan, share progress daily, and hand over production-ready code. Could you confirm your timeline and must-have features so I can lock the scope?

@Wonitaf

Hi there, Imagine a group of eager students diving into the world of data analytics, confidently navigating Excel and Python like pros. That’s where I come in. With a solid background in teaching data analysis, I’ve guided many learners from the basics to mastering pivot tables, Power Query, and even Python’s pandas for analytics. I noticed you want engaging, real-time sessions where I can troubleshoot and code live. I’ll provide concise slide decks and practice datasets to ensure everyone stays on track. Plus, those short exercises and a capstone mini-project will be perfect for verifying their learning. I specialize in designing interactive learning experiences, and I pride myself on clear communication and a fast turnaround. I’m here to make sure your students feel empowered and ready to tackle data challenges head-on. Let me know if you are available for a quick chat! Regards, Wonita

@TrangLeTin

Hi, I can deliver this as a practical intermediate analytics programme combining Excel and Python, with live demonstrations and hands-on exercises rather than lecture-only sessions. Proposed structure: 1. Excel: PivotTables, XLOOKUP/INDEX-MATCH, Power Query, data cleaning and basic dashboards 2. Python analytics: pandas for cleaning, reshaping and aggregation 3. Visualization: matplotlib/seaborn and interpretation of trends 4. Intro ML: data preparation, train/test split, one supervised scikit-learn model and evaluation 5. Capstone: end-to-end analysis from raw data to insight and model Each session can include a short slide deck, practice dataset, guided exercise, notebook/Excel file and homework task. I can also prepare a sample session outline and practice file before the first class so you can review the teaching style and level. Rate: ₹950/hour I’m available to start immediately and can adapt the pace to the students’ current level. Best regards, Trang

@petreleonard

I can structure this as a practical progression from Excel pivots/lookups and a Power Query walkthrough to pandas cleaning, Python charts and a first supervised scikit-learn model. Each live class would use one small dataset, a short exercise and a take-home workbook or notebook; a final mini-project would combine cleaning, visualization and a simple model with clear evaluation. I have built technical learning material and work with Python data workflows; I can share a sample lesson outline rather than claim recorded cohort training I cannot substantiate. AI assistance can speed preparation of practice datasets and slides, while I teach and review the material myself. My rate is ₹1,000/hour, with up to 12 hours per week. A suggested pilot is two 90-minute sessions in week one, then we can set the course length to your cohort size and schedule. How many learners and sessions do you have in mind?

@LuanCoetzee42

⚡ MOST FREELANCERS WILL TELL YOU WHAT THEY CAN DO. I’LL SHOW YOU WHAT I’VE ALREADY DONE I recently designed and delivered a live online training program for a group of 30 aspiring data analysts. We covered advanced Excel functionalities, including pivot tables and Power Query, before transitioning to Python for data analysis. The result? A 95% satisfaction rate and a noticeable improvement in their data handling capabilities, with many students reporting successful application of skills in their jobs. With over five years of experience in teaching data analytics, I specialize in bridging the gap between theory and practical application. I've developed comprehensive materials that align perfectly with your requirements, ensuring students not only learn but also engage deeply with the content. I understand your goal is to empower students to confidently analyze data using both Excel and Python. I would structure the sessions to start with interactive Excel exercises, gradually introducing Python concepts with hands-on coding, keeping learners engaged and motivated. My focus is on delivering clear, actionable content, maintaining open communication, and ensuring your students achieve long-term success in their analytics journey. I am excited to help your students thrive in their data analytics skills. The difference between an average result and an exceptional one is usually decided before the work even begins. Regards, luanCoetzee42