Business Analysis: Fill & Download for Free

Being a developer means you already have system knowledge, all you need is to start learning more about domain process and documentation part (which also includes tools like m visio for process flow and refers some sample document for preparing BRD)one piece of advice due to strong system knowledge try for system business analyst.Cheers and feel free to ask any doubts you have.

Chatbots, also called Conversational Agents or Dialog Systems, are a hot topic. Microsoft is making big bets on chatbots, and so are companies like Facebook (M), Apple (Siri), Google, WeChat, and Slack.I have done little research on the deep learning chatbot service resources during early 2017. I can recommend you few of them as per my research knowledge in chatbot. (These aren’t official rankings of chatbots.)Microsoft AzureDescription : (LUIS)Language Understanding Intelligent Service for building chatbot using visual or node.js in backendFunctionality: Congnitive Service which provide APIs for language understanding and Knowledge Extraction, Speech API for Speech recongnition and conversion, Bing Search APIs for intelligient web search capabilities, Vision API for image and video understaind skill.Voice & Text Support: YesNLP (Natural Language Processing): YesNLU (Natural Language Understanding): YesNLG (Natural Language Generation): NoMachine Learning: YesSpeech Recognition: YesSpeech Language Understanding (SLU): YesConversation Support: YesPredefined information: YesGap Analysis: NoCross platform support: YesUsability: Easy but very slow. Sometimes needs to refresh a page more then once to see created intents and Utterances on browser. Developers can also use Visual studio to develop chat-bot using coding in C#. There is Bot emulator service where we can test the bot. It’s tough for non-developers to use this service.Ease of modeling: EasyEase of training: EasyEase of integration: SDKsPerformance: Slow user InterfaceAnalytics: Dashboard shows analytics.IBM WatsonDescription :Several different AI-based APIsFunctionality: NLP, Speech-to-Text, Text-to-Speech, Discovery, and moreVoice & Text Support: Watson requires a separate service: Watson Speech to TextNLP (Natural Language Processing): YesNLU (Natural Language Understanding): YesNLG (Natural Language Generation): NoMachine Learning: Yes, cloud-basedSpeech Recognition: YesSpeech Language Understanding (SLU): NoConversation Support: Yes, requires state storagePredefined information: YesGap Analysis: YesCross platform support: YesLocalizability: YesUsability: Low barrier to entry. "Training" the intelligence and creating "scripts" can be done by non-developers.Ease of modeling: EasyEase of training: EasyEase of integration: EasyReliability: Top-Tier (IBM-based)Performance: Top-Tier (IBM-based)Supportability: Top-Tier (IBM-based)Scalability: Top-Tier (IBM-based)Price: https://www.ibm.com/watson/developercloud/conversation.html#pricing-blockAmazon Alex (Services are expensive compare to IBM and Microsoft)Description : AWS service for building conversational interfaces into applications using voice and textVoice & Text Support: YesNLP (Natural Language Processing): YesNLU (Natural Language Understanding): YesNLG (Natural Language Generation): ?Machine Learning: Deep LearningSpeech Recognition: Yes (Automatic Speech Recognition ASR)Speech Language Understanding (SLU): Yes (ASR + NLU)Conversation Support: YesPredefined information: YesCross platform support: Yes. Mobile devices, web applications and chat platforms.Ease of modeling: EasyEase of training: EasyEase of integration: AWS Lambda, Cognito, Mobile Hub, CloudWatch, DynamoDBSupportability: Depending on our AWS support contract, Amazon Lex is supported under Developer Support, Business Support and Enterprise Support plans.Price: Amazon Lex Pricing - Amazon Web ServicesWit (Facebook)Description : Natural language for DevelopersVoice & Text Support: NoNLP (Natural Language Processing): YesNLU (Natural Language Understanding): YesNLG (Natural Language Generation): NoMachine Learning: Deep LearningSpeech Recognition: NoSpeech Language Understanding (SLU): NAPredefined information: YesCross platform support: YesEase of training: EasyAPI.aiDescription : Natural language understanding platformFunctionality: Congnitive Service which provide APIs for language understanding and Knowledge Extraction, Speech API for Speech recongnition and conversion, Bing Search APIs for intelligient web search capabilities, Vision API for image and video understaind skill.Voice & Text Support: YesNLP (Natural Language Processing): YesNLU (Natural Language Understanding): YesNLG (Natural Language Generation): NoMachine Learning: Yes, Learn from examples provided by developers and conversations it has with end users to continuously improve user experience.Speech Recognition: YesConversation Support: Switch between conversation topics, while remembering where you left off for each one.Predefined information: YesCross platform support: Yes, SDKs for iOS, Mac OS X, Apple Watch, Android, HTML, JavaScript, Node.js, C#, Python, Unity, Ruby, XamarinUsability: Easy. Support for 15 languagesEase of modeling: EasyEase of training: EasyEase of integration: Integrations | API.AI (webhook tool, SDKs)Reliability: 99.99% guaranteed uptimePerformance: can handle millions of user requests dailyAnalytics: Yes

Without a doubt, computational thinking.See http://www.cs.cmu.edu/~CompThink/, http://www.google.com/edu/computational-thinking/, and http://en.wikipedia.org/wiki/Computational_thinking. See http://www.cs.cmu.edu/~wing/publications/Wing06.pdf for the seminal paper on computational thinking.@article{Wing2006,  Address = {New York, {NY}},  Author = {Wing, Jeannette M.},  Doi = {https://dx.doi.org/10.1145/1118178.1118215},  Journal = {Communications of the {ACM}},  Month = {March},  Number = {3},  Pages = {33--35},  Publisher = {{ACM} Press},  Title = {Computational Thinking},  Url = {https://dx.doi.org/10.1145/1118178.1118215},  Volume = {49},  Year = {2006}} That summarizes a lot of the platform-independent skills that students can acquire in a decent undergraduate engineering (especially those in electrical and computer engineering, ECE) or computer science (CS) degree program.You learn how to solve problems cheaper, faster, and better than many of your peers. Algorithm analysis help you determine the resource consumption, cost, and quality of your solutions. You also learn to determine which problems are solvable given current or soon-to-be-available technology, and which problems can never be solved.You also learn how to develop mathematical and computational models for the problems that you are solving as well as systems/networks that you are analyzing so that you can obtain some quantitative/simulation/experimental results concerning the problems/systems/networks. This allows you to take a computational/engineering approach to any academic field. For example, you can work on: behavioral informatics, computational agriculture, computational archaeology, computational biomechanics, computational cognitive science, computational economics, computational forensics, computational linguistics, computational materials science, computational physiology, computational photography, computational philology, and computational sustainability. This builds up your breath of skills and knowledge, regardless of whether you have to take electives or mandatory classes outside of engineering and CS. Also, you can work on interdisciplinary fields that favor those with skills and knowledge in engineering, mathematics, and CS. For example, the pioneers of contemporary/modern approaches to complex systems were physicists (Albert-László Barabási, Réka Albert, Duncan J. Watts, Steven Strogatz). When Jon Kleinberg and, later on, Jure Leskovec came along, they were able to advance the field much further.While modeling, you learn that nonlinearities are terrible to deal with, so you learn to design your systems, networks or circuits to operate in the linear mode of operation, and use the principle of superposition to determine the system response. Else, you would use appropriate approximation techniques to linearize the nonlinearities or use a combination of linear models to approximate the nonlinearities (e.g., see Trajectory Piecewise Linear Model Order Reduction). Also, you get exposed to the concept of duality. If you can't find a solution using the circuit, network, or formula (based on mathematical logic), the dual of that circuit, network, or formula may be able to solve the problem.You develop good logical and quantitative reasoning skills, and develop methods to automate logical and quantitative reasoning. For example, you can use mathematical logic (e.g., first-order logic or temporal logic) to express properties about a system, and use decision procedures or theorem provers to reason on these properties. Or, you can use a solver for satisfiability modulo theories to determine if the set of properties are compatible. In addition, you can model a system/network with a very-large-scale matrix equation, and use model order reduction to simplify the mathematical model of the system/network. You can use numerical techniques, such as ODE/PDE solvers, to analyze models of biological systems/networks. Moreover, you learn to automate as many tasks as you can, especially things that you would do on a computer or smart phone.You can exploit your skills in engineering and CS to gain advantages in many of your endeavors. Hence, this leads to better life hacks and travel hacks. For example, you learn to pipeline your tasks, carry out as many tasks in parallel as possible, efficiently allocate resources, and attempt to reduce the duration and costs of your critical paths in project management or in your hardware/software... Speaking of hacking, you can also use your skills to come up with better pranks. Look up "MIT hacks".Your repeated endeavors in verifying, testing, and validating what you develop in engineering or CS help you become more aware of security loopholes. Hence, you can take a more holistic approach to securing your computer, smart phone, house/apartment, dorm room, and your workspace (at work or research lab). You can take a more holistic approach to evaluating the quality of products. ISO certification would not suffice. You would attempt to tinker with the product to determine how reliable, safe, and good it is. Automatic test pattern generation (or automatic test input/case generation) can help you trigger sensitivities in people to reveal their motives/intentions and bias/prejudice. Assume that they have a fault (a particular evil desire or bias). Exploit your knowledge about them to get them to become worked up about that fault; fault activation. Use directed questions to guide them into revealing that fault: fault propagation.You learn how to store information in efficient ways, in terms developing data structures to store information for computation and for knowledge/resource management in your daily life. For example, you may invest in a good reference management software and LaTeX to help you manage information resources or knowledge that you acquire.Learning about the theory of programming languages (in the context of theoretical CS) helps you to appreciate the language classes (e.g., English or Italian) that you have taken (and are taking), such as lessons on grammar.Learning about computer systems organization and computer architecture expose you to pipelining and parallel computing (also, see concurrent programming). These concepts can be exploited in your daily life to maximize the amount of tasks completed in a given time frame, and/or utilization of resources in your home, workplace, school, or elsewhere.You learn to apply search and optimization techniques to obtain better outcomes than others in sports, games, business/project management, or finding eating outlets of a particular cuisine.You have a better propensity of keeping up to date with advances in technology. For example, you exploit the use of analytics for data mining to improve business analysis or to figure out who is stalking you. Similarly, you can use cloud computing to reduce your expenses on computer hardware and store information on the cloud for backup and remote access. Instrumentation and data acquisition helps you figure out how to connect and set up equipment, computers, and electronic products. This can come in handy in home improvement or setting up your workplace.You take advantage of your skills in abstraction, encapsulation, hierarchical design, component-based design, and platform-based design to understand systems, processes, and networks, and exploit that knowledge to your advantage. For example, you make understand how the coupling of certain modules can render the system to be unreliable, and attempt to reduce their dependencies. Or, you can isolate certain components/modules in your system to improve fault isolation. When it comes to interior architecture and home/building design, you learn how to set up certain systems/processes to target hubs in social networks to take down terrorist networks, or isolate cliques to reduce the spread of infectious diseases. In addition, they help you understand the importance of paying attention to the dynamical interactions (especially, if they are strongly nonlinear and are distributed) between entities in a network or components of a system, or between the system/network and its environment. Such dynamical interactions can improve feedback in an organization or system to improve its reliability and stability. On this note, classes in control engineering help you utilize feedback in systems, networks, processes, and organizations to meet your objectives, such as reliability and stability.Software development processes/models, such as agile methodologies (e.g., eXtreme Programming, XP), help you to emphasize values (or good attributes) over traditions (particularly those that are discriminatory or exploit certain social groups). For example, with XP, you value communication, simplicity, feedback, courage, and respect over pride, ego, bias/prejudice, and any given engineering or software development practice. You learn to embrace continuous and incremental improvement over a set of practices and traditions that a significant amount of people stubbornly hold on to. Classes concerning quality control would also emphasize continuous refinement.Signal processing introduces you to the need to filter off noise and distortion from your signals. In daily life, that can refer to using your analytical and reasoning skills to detect and filter off lies and rumors. Error detection and correction help you appreciate humans' natural abilities to detect grammatical errors, false claims, and lies in conversations or publications, and automatically correct them.Telecommunications and computer networking exposes you to efficient information transfer. For example, you learn how to transmit information or send items/gifts in a cost-effective manner between any pair of locations (source and destination), individuals (sender and receiver), or groups of people (transmitting group and receiving group).Electronic design automation (EDA) exposes you to synthesizing integrated circuit designs from a model/design at a higher level of abstraction. See logic synthesis, high-level synthesis, and analog/RF and mixed-signal circuit synthesis. From this, you learn to automatically transform simplified models of systems into (final/actual) implementations of your designs. This helps you go from analyzing models of systems and networks to producing working/functional prototypes of your products. So, you can proceed from analyzing a simple model of the economy to obtain financial products that people may invest in. From logic synthesis, you learn how to automatically select and connect components from a library/set/collection to implement systems/networks that satisfy design objectives and constraints. This technique can be applied to other areas, such as synthetic biology.EDA also exposes you to partitioning, which can be employed to transform monoliths into a system/network of components that can be analyzed or manipulated with greater ease. In addition, EDA exposes you to floorplanning, which introduces you to automatic procedures for planning the design of your (electronic) system or your house (floorplanning in the context of building/landscape/interior architecture). Extraction exposes you to automatically obtain the important information about a circuit, system, network (or process) so that you can analyze the simplified model (that you extracted) faster.Concerning students studying in rigorous engineering and CS programs, they get to develop the following non-technical skills, possibly better than other students. You learn to manage a ridiculous academic workload, on top of your other responsibilities and desired activities. This usually involves some body hacking via the consumption of copious amounts of coffee, tea, or energy drinks (such as Red Bull or Rockstar) to pull all-nighters and keep late nights.You learn to be more efficient and effective in doing things. When you take easy classes, regardless of whether they are electives or mandatory classes, outside of engineering and CS, you would dominate your classmates without engineering or CS backgrounds. You learn to produce academic output (papers, project reports, presentations) of better quality at a faster pace than others. Yes, do it cheaper, faster, and better.You learn to improve your multicultural skills, since you have plenty of opportunities to meet and interact with others of different cultural backgrounds. When you are pressed for time in tense situations, such as hacking on your project during an all-nighter, you learn to forgive easily and move on, and address miscommunication quickly. Over time, you learn to value diversity and inclusiveness, which can help you overcome common cause/mode failure since a diverse group of people can look at a problem/system/network with more perspectives.