You want to learn data analytics for Product Management. What are the best courses?

Data analytics is a core skill for a product manager - a PM needs to be looking at product & business data on a daily basis. PMs need data for: 1. Identifying the potential consumer pain point e.g. high TAT for shipment delivery, low CSAT, etc. 2. Identification of friction points in user journey e.g. high bounce rate, funnel drop off, low task success rate, etc. 3. Creating business case for investment: Analyzing data to estimate impact for feature to be built. This helps aligning senior stakeholder for investment decision 4. Tracking impact: Once the feature is launched, a PM needs to measure metrics to see if the desired impact is delivered. This also helps in further removing friction from user journey

Embark on the transformative journey of merging intuition with insights by delving into data analytics for product management. Think of it as adding a compass to your product strategy, navigating decisions with data-driven precision. Unleash the power of courses like Google Analytics for Beginners or Data Science for Product Managers; they're not just classes but voyages into a realm where understanding user behavior and market dynamics becomes a second nature. It's not merely learning; it's sculpting your product management acumen into a masterpiece, where each data point paints a clearer picture of success.

Boost your product decisions with data! Level up your game with "Data Science for Product Managers" on Coursera, master user insights with "Google Analytics Certification," and refine strategy with "Data Analytics for Managers" on edX. These 3 practical courses unlock the power of data for smarter product choices. Invest in your skills & build winning products!

Some of the Free Tools are listed below: 1. Simplilearn: They offer a free Data Analytics Course with a certificate & is conceptually good for beginners to intermediate. 2. CareerFoundry:They provide a free tutorial for beginners in data analytics & what a data analyst actually does. 3. GeeksforGeeks For paid courses 1. Become a Data Driven Product Manager : This course on Udemy focuses 100% on data for PMs & topics like defining success metrics, A/B testing, data-driven solutions,etc 2. Product Analytics Micro-Certification (PAC) 3. You can find many Data Analytics for PM courses on LinkedIN learning. Remember, the best way to learn is by doing. So, try to apply what you learn in these courses to real-world scenarios. Happy learning! ??

Data analytics is essential for product management as it provides actionable insights into user behavior, market trends, and product performance. It enables informed decision-making, effective prioritization of features, and the ability to optimize the product based on real-time feedback. Data-driven product management leads to better user experiences, increased customer satisfaction, and higher chances of success in the competitive market.

Knowledge of tools like Google Analytics or Tableau is invaluable for interpreting user data and translating it into actionable insights. For instance, a product manager might use these tools to track user engagement metrics on a new app feature, identifying usage patterns and areas for improvement. Additionally, skills in A/B testing and interpreting the results can guide feature enhancements, ensuring decisions are data-driven and aligned with user needs and business goals.

Data analytics skills for product management include: Data Interpretation: Ability to extract insights from data. Statistical Analysis: Understanding statistical methods. Data Visualization: Presenting data effectively. SQL: Querying databases. A/B Testing: Conducting experiments. Business Acumen: Connecting data to business decisions. Communication: Explaining findings to non-technical teams. Tools: Proficiency in analytics tools like Excel, Python, or Tableau.

Excel has no boundaries PowerBi and SAP are great tools we should all learn There are data management and visualisation softwares like Qliksense For dashboard creation Tableau and these kind of visualisation softwares are good to learn

Whether you're a from software engineering background or a business maven turned Product Manager, mastering data analytics is essential. For my fellow techies, Python, NumPy, and Pandas are your trusty allies, turning data manipulation into a breeze. On the flip side, if you're from a business background, Excel and tools like Power BI and Tableau are your go-to weapons for crafting insightful reports. Here's a pro-tip: Dive into public datasets regularly! ???♂? It's like a workout for your data muscles. The more you flex them, the sharper your intuition becomes. If you do this consistently, you will see that you would gain that extra edge in making killer product decisions. Instead of memorizing analysis frameworks play with real data.

Integrated Skill Development: Master both technical (data analysis, visualization) and business skills (data literacy, critical thinking) for comprehensive data analytics proficiency. Technical Foundation: Build expertise in data collection, cleaning, and interpretation, laying the groundwork for extracting meaningful insights. Business Acumen in Data: Elevate business skills by understanding data in context, emphasizing critical thinking, ethics, and privacy considerations. Strategic Data Integration: Align data analytics directly with the product's vision, strategy, and roadmap for impactful decision-making.

I won't provide you with a list of random courses on the internet; you can find them easily through a simple Google search or ChatGPT. Instead, I will guide you on the type of course you should consider based on your background. If you come from a business background, I recommend mastering your Excel skills, since if you haven't delved into coding or scripting before, mastering these skills will require time and effort on your part. Excel, being a tool you're likely already familiar with, is a more accessible option. There are numerous courses available online. Software engineers turned product managers, enhance your Python scripting skills, exploring libraries like NumPy, Pandas, and Jupyter Notebook. Excel is also a valuable option.

To learn data analytics for product management: 1. Master tools like Excel, SQL, and data visualization software. 2. Take online courses on data analysis and interpretation. 3. Analyze real-world data sets to make data-driven decisions. 4. Learn to create and interpret key metrics. 5. Collaborate with data scientists and engineers to harness data insights for product improvements. 6. Stay updated on data trends and technologies to enhance product management skills.

Learn data analytics for product management through diverse avenues: - Online Courses: Explore self-paced or instructor-led courses covering a range of topics and skill levels. - Bootcamps: Opt for immersive, short-term programs offering hands-on projects, mentorship, and career support. - Books and Blogs: Delve into theoretical and practical knowledge with examples, case studies, and best practices. - Podcasts and Webinars: Absorb insights and experiences from experts and practitioners, gaining tips, trends, and stories. Choose the method that suits your learning style, budget, and schedule for a well-rounded education in data analytics for product management. ?????? #DataAnalyticsLearning #ProductManagement #DiverseAvenues

1. Online Courses: Platforms like Coursera, edX, and Udacity offer numerous product management and data analytics courses. Specialization options, like Google's "Data Analytics for Product Managers" on Coursera, provide focused learning paths. Consider shorter, focused courses on specific skills like SQL, data visualization, or basic Python for data analysis.

?? Learning data analytics for product management offers a plethora of avenues catering to diverse preferences and circumstances. Online courses, ranging from self-paced to instructor-led formats, furnish comprehensive coverage of topics at various proficiency levels. Alternatively, bootcamps offer immersive, hands-on experiences supplemented by mentorship and career guidance within condensed time frames. ??? Delving into books, blogs, podcasts, and webinars unveils a wealth of theoretical frameworks, practical applications, and industry insights. These resources, enriched with examples, case studies, and expert perspectives, foster continuous learning and exploration.

Learning Objectives > A Given Course As a PM what would you like to be able to do, analytics-wise? I teach in an MBA program within the Quantitative Analytics area. We think about this. Here's a point of view: "After your analytics course [whatever it is], you should be able to: 1. explain the difference between a dependent and independent variable 2. distinguish between associative (correlated) inferences vs. causal inferences 3. understand core descriptive statistics (mean, median, standard deviation) 4. frame hypothesis testing with frequentist methods 5. use Python to organize data for analytics I recommend a combo of 'Agile Analytics & AI' on Coursera and also 'Python for Data Science and Machine Learning Bootcamp' on Udemy.

N?o existe uma classifica??o de qual é o melhor curso. Uma vez que você está buscando uma nova área de conhecimento, recomendo buscar cursos rápidos de baixo custo para ter um progresso de conhecimento crescente. Busque cursos em plataformas como Udemy e DSA (Data Science Academy).

Before jumping into a data course, build your foundations by understanding the basics of data. Basic statistics like mean, median, deviation, regression, etc. Understand how data is stored, collected and analysed. You will get most out of your data analytics courses if you have a solid foundation.

Learning data analytics for product management is a valuable skill that can improve your ability to make data-driven decisions and optimize product performance. Here are my personal recommended courses that can help you build a foundation in data analytics for product management: 1. Google Analytics Academy: Google Analytics for Beginners. This free course by Google covers the basics of Google Analytics, providing a solid foundation for understanding user behavior and website performance. I highly recommend this course, and if you are eligible, there is an option to apply for aid and get it for free. 2. LinkedIn Learning: "Learning Data Analytics". This is a great option if you already have LinkedIn Premium.

There are many options when it comes to Data Analytics course. Listing out some free courses: - Google Analytics Certification (Beginners + Advanced) covers all the basics of data analysis & visualization - Courses on Coursera (DS orientation by IBM, Marketing Analytics by University of Virginia) - Courses on edX (Data analytics in Product Management) - Tableau analyst certification: Very detailed course focused on data visualization

To choose the right data analytics course for product management: 1. Look for courses that cover both data analysis and product management topics. 2. Check if the course offers hands-on projects to apply skills. 3. Ensure it covers relevant tools like Python, SQL, and data visualization. 4. Consider courses from reputable platforms like Coursera, edX, or universities. 5. Read reviews and seek recommendations from professionals in the field. 6. Align the course with your career goals and level of expertise.

Assess your current skill level and needs. Define your learning goals. Evaluate the course content and structure. Consider the instructor's expertise and experience. Compare different platforms and pricing. Leverage trial periods and free resources.

When picking a data analytics course for product management, start by reflecting on your skills and how you learn best. Consider factors like cost and time commitment, but also prioritize courses with engaging instructors and interactive content. Look for real-world examples and projects to make learning practical and enjoyable. Seek recommendations from peers or professionals in the field to ensure you're choosing a course that's respected and valuable. Trust your instincts and choose a course that feels right for you.

?? Selecting the ideal course for data analytics in product management hinges on a thoughtful evaluation of several key factors. Begin by assessing your existing skill set and identifying areas for growth to pinpoint the most suitable course level and content depth. Consider your preferred learning style, whether it's self-paced exploration or structured instruction, to align with a course format that resonates with you. ?? Additionally, weigh the costs and duration of available courses against your budget and schedule constraints. Opt for a course that offers the best value proposition while fitting seamlessly into your lifestyle.

I recommend taking a course specifically regarding how to Tell a Story with Data. Oftentimes, we can be very good at pulling facts and figures, but we need improvement in making connections with that data and, better yet, how to tell an unbiased, and impactful story to our stakeholders.

Spice up your data analytics journey with these interactive approaches: Data Playground Challenge: Team up, pick a product (real or imagined), collect data, and "escape" by solving challenges and presenting your findings in a creative way. Data Detective Escape Room: Become data sleuths! Crack puzzles, analyze datasets, and "escape" a themed room by solving product-related data challenges. Product Analytics Hackathon: Compete in teams to build dashboards, design A/B tests, or craft data stories. Win prizes for creativity, impact, and data skills. Data Visualization Showdown: Master data storytelling! Present your analysis with captivating visuals, compete for votes, and learn from each other's approaches.

I recommend identifying your goal first, e.g., being an AI product manager and mobile PM is a slightly different experience that requires different data analysis tools vs. metrics. Also, explore what tool's stack is in use at your organization, e.g., if you use Google Analytics, then it's worthwhile to take their domestic courses. All of this will assist you in selecting a course tailored to your specific needs. Overall, surf these platforms: Coursera, Udemy, edX, Udacity, and LinkedIn Learnings. Make sure you pay close attention to course reviews and content to ensure you choose the most suitable option for your situation.

There must be several good quality courses available out there. Some are mentioned in the contributions above too. But here’s the deal - Any good data analytics course should include learnings on how to look at & interpret data. Not just extracting and compiling it. Unless a course covers how to draw actionable insights from data, it will be a partial learning. I took one a few months back named “data for PMs”. It is listed in my profile for reference as well. Hope this helps!

The "best" course is the one that aligns with your individual needs, goals, learning style, and budget. Don't hesitate to ask questions and research your options thoroughly before making a commitment. Continuous learning is key in this field, so be prepared to stay updated and expand your skillset over time

Quick responses don't always yield the best results, especially for analytics learning. Here's my condensed advice for picking the right course: - First master basic principles, not tools. Tool-centric courses often exist due to corporate promotion. Without concept comprehension, Excel becomes merely a calculator, Power BI just a viewer. Also, organizations vary in tools used, potentially rendering your tool knowledge moot. - Choose your teacher carefully. People learn differently. Preview lessons and read reviews before course investment. - Find a mentor. Their experience can help you concentrate on essentials and bypass unnecessary steps.