Boost your Skills by learning: Digital Marketing
Table of Contents:
Artificial Courses with Job Ready Intuitive after the 12th:
Artificial Courses with Job Ready Intuitive after 12th:
1) Safalta Course:
This Digital Marketing Course contains Live Classes, PDF Notes, Question and answer Sessions, Case Studies, and much more.
Source: Safalta
It includes both principles and an in-depth understanding of all Digital Marketing specializations.The Most Important Points
- Complete Placement Assistance
- Google Certified Experienced Professors
- ten modules based on industry
- 8+ ongoing projects and case studies
- 20+ Learning Resources
- 150 hours of live teaching in addition to conceptual lectures
- Complementary soft skills training
- Weekly question-and-answer session
- Masterclasses with industry specialists
Modules:
Module 1: Marketing Research Overview
- Marketing Fundamentals and Digital Marketing
- Why would you engage with online advertising instead of conventional marketing?
- Opportunities for Employment in Digital Marketing
- Examples of Digital Marketing Case Studies
Introduction:
- Websites: An Overview
- Website Categories
- Protocol, Server, Domain, and SSL Overview
- WordPress Introduction and Installation
- Theme and Plugin Installation
- Blogspot Websites WordPress Website Design
What Is Google Search
- How Does It Work?
- SEO Case Study
- Introduction to Search Engine Optimisation
- Types of SEO
- An Overview of On-Page SEO
- Meta Tag Optimisation (Meta Description, Meta Title)
- Image Alt Text, Heading Tags, Anchor Text, and Internal/External Linking are all examples of content optimization.
- Crawling and indexing optimization (Sitemap.xml, Robots.txt)
- An Overview of Keyword Research
- Keyword Research Instruments
- Off-Page SEO Fundamentals
- The Backlinks and Link-Building Concept
- Backlink Varieties
- Link-Building Strategies Based on Content
- Google Search Console Overview
- Configuration of Google Search Console
- KPIs for Google Search Console
- Analysis and Reporting of Organic Data
- Introduction
- Fundamental Writing Skills
- How to Find Popular Content Ideas
- Writing Capabilities
- Identification of Duplicate Content
- Cluster of Contents
- Guest blogging
- An Overview of Social Media
- A Guide to the Leading Social Networking Networks
- Case Studies in Social Media Marketing
- Meta Business Suite: An Overview
- Creating and Sharing Groups
- Page Creation and Optimisation on Facebook
- Making and Improving Your Instagram Professional Account
- Content Suggestions and a Profile Grid
- Ideas for Reels, Hashtags
- Twitter Profile Development and Optimisation
- Retweets and Growth Suggestions
- Create and Optimise Your LinkedIn Profile
- How to Set Up a LinkedIn Company Page
- How Can You Expand Your LinkedIn Connections?
- YouTube Creator Studio Overview
- YouTube Channel Development and Optimisation
- What is the best method for uploading and optimizing videos on YouTube?
- Canvas concept
- An Overview of Social Media Ads
- Structure of Paid Advertisements
- Manager of Meta Ads
- KPIs for Social Media Ads
- Ads on Facebook
- Instagram advertisements
- Introduction
- Search Engine Marketing Overview
- Google Ads Concept:
- Discuss the many types of advertisements.
- Bidding Strategies Explained
- Structure of an Ad Campaign Introduction
- Google Ads KPIs
- Creating Google Search Ads
- Making Google Display Ads
- Creating Google Video Ads
- Types of Keyword Matches
- Google Analytic
- Google Analytics Explained
- Setup of a Google Analytics Account
- Google Analytics Key Performance Indicators
- Reporting and Analysis of Web Traffic
Google AdSense:
- An Overview of Google AdSense
- Setup of a Google AdSense Account
- How to Obtain AdSense Acceptance
- Affiliate Marketing Explained
- Create an Amazon Associates Account
- Introduction
- Introduction to Email Marketing
- How Email Marketing Helps Business Grow
- Create Professional Email Account
- Concept of Bulk Emails
- Email Marketing Templates and Content
Job Search Preparation:
- Creating a Resume
- How to Find Digital Marketing Jobs
- Indeed, Create Profiles on Naukriit
- An Overview of Freelancing
- How to Look for Freelance Work
- Create Freelancer, Upwork, and Fiverr profiles.
2) Artificial Intelligence Professional Certificate in Computer Science:
Harvard's CS50 computer science course is one of the greatest popular CS online courses accessible today. This two-part professional credential from edX follows Harvard's CS50 and CS50AI courses, enabling learners without prior CS experience to enter the field of AI. AI is a branch of computer science, therefore understanding standard CS ideas is essential for knowing how to create intelligent systems. The professional certificate requires completion of both courses, however, if you already feel confident in your CS expertise, skipping to the second course may be a better match and save you time. Even though this course includes parts on C and Python programming, I wouldn't call it an introduction to programming. It may be difficult to keep up if you are not already familiar with a programming language.
Syllabus:
Course 1: Computer Science Fundamentals
- Introduction to Computer Science
- C is a programming language.
- Operators, conditional expressions, loops, and command line
- Variables, functions, diagnostics, arrays, and command-line arguments
- Algorithms
- Linear search, binary search, bubble sort, selection sort, recursion, and merge sort are all examples of search methods.
- Pointers, custom types, dynamic memory allocation, call stacks, and file pointers are all examples of Hexadecimal memory.
- Singly-linked lists, hash tables, and attempts are examples of data structures.
- Python is a programming language.
- Using SQL in Python Web Development
- Internet basics, IP, TCP, HTTP, HTML, CSS, JavaScript, and DOM
- Ajax and Flask web servers
- Searching for answers to challenges
- Knowledge is the ability to represent information and draw conclusions from it.
- Uncertainty - dealing with uncertain occurrences using probability
- Learning is the use of data to enhance performance.
- Neural Networks are computer programs that use brain-like architecture to execute tasks.
- Language - processing genuine human language
3) Jaipur National University, BCA Artificial Intelligence:
The Bachelor of Computer Application in Artificial Intelligence degree is a three-year study that provides students with the information and abilities needed to create AI software. The course focuses on teaching a range of programming languages and technologies that are required in the construction of AI machines and algorithms. As a result, various machine learning disciplines are incorporated into the course curriculum. Job options for students who complete such AI courses after high school include positions such as software engineer, IT analyst, AI engineer, big data analyst, and AI architect.
Eligibility:
- 10 plus two or its equivalent with at least 50% grades.
- Duration: three years
1) Best 5 Benefits of AI-Powered Conversion Rate Optimization (CRO)
2) Can the Search Engine detect AI Content?
4) MIT xPro: Designing and Building AI Products and Services:
Discover the four stages based on artificial intelligence product design, the principles of machine and deep learning algorithms, and how to use the insights to address real-world challenges. Students can develop an AI-based product proposition to submit to company executives and investors. UI/UX designers, technical product managers, IT specialists and consultants, entrepreneurs, and AI company founders are required.
5) TensorFlow introduction for Machine Learning, Deep Learning, and AI, via Coursera:
Deeplearning.ai's four-course certificate program teaches best practices for utilizing TensorFlow, an open-source machine learning framework. Students will also learn how to build a simple neural network in TensorFlow, train neural networks for computer vision applications, and enhance their neural networks with convolutions. This is one of four courses included in the DeepLearning.
Professional Certificate in AI TensorFlow Development. Prerequisites: Software developers interested in creating scalable AI-powered algorithms. High school-level maths and Python coding knowledge are necessary. Prior experience in machine learning or deep learning is advantageous but not needed.
6) Reinforcement Learning in Python (Udemy):
Important components: This course will teach you how to apply gradient-based machine learning models with supervision to reinforcement learning, as well as how to construct 17 different reinforcement learning algorithms and use the OpenAI Gym toolbox with no code modifications. The following subjects are also addressed: The multiarmed bandit problem and the explore-exploit dilemma; Markov decision discrete-time stochastic control processes; methods for calculating means and moving is typical and their relationship to stochastic gradient descent; and proximity methods, such as how to plug a deep neural network or other distinguishable model into a reinforcement learning algorithm.
Calculus (derivatives), probability/Markov models, Numpy coding, Matplotlib Python visualizations, expertise with supervised machine learning algorithms, linear regression, gradient descent, and solid object-oriented programming skills are required. Students and professionals who are interested in AI, data science, machine learning, and deep learning can enroll in the course.
The word "artificial intelligence" conjures up images of humanoid machines like those seen in Westworld and Ex Machina. Although it is now impossible, this advanced type of AI, technically known as Artificial General Intelligence (AGI), is being extensively researched. Artificial specific Intelligence (ANI), or AI systems that specialize in specific tasks such as autonomous driving, Starcraft, and arguing humans, has witnessed significant breakthroughs in AI. Andrew Ng, a famous machine learning specialist, explains why AGI has made less progress in compared to ANI in his course, AI for Everyone. Because practically all online AI schools cover limited intelligence, the majority of this piece will focus on suggested ANI courses.
Read More: How AI will Create More Jobs in India by 2025
What is the best route for artificial intelligence after the 12th grade?
After high school, you can pursue a bachelor's degree in subjects such as computer science, data science, or AI.
What should I study for AI jobs?
Undergraduate degrees in computer science or engineering are a wonderful place to start, but a master's degree in artificial intelligence may give you personal experience and expertise from industry specialists, helping you acquire a career and distinguish yourself from other candidates.
How can I acquire a career in artificial intelligence?
Obtain a degree. Most AI occupations will demand a bachelor's degree or above. Some entry-level occupations may need only an associate degree or no degree, however, this is unusual. Most people who work in AI have a bachelor's degree in computer science, mathematics, or a related discipline.
How much does a BTech in artificial intelligence pay?
In India, the average annual salary for a B. Tech in Artificial Intelligence and data science is 10.0 lakhs, with incomes ranging from 4.0 lakhs to 37.9 lakhs. This average pay estimate for AI and DS engineers is based on the earnings of 211 most recent graduates from the leading universities for B.
Is it simple to find work in artificial intelligence?
All AI practitioners, however, must have a solid basis in computer science, software, and conventional programming languages. A master's degree is required for the majority of the highest-paying artificial intelligence employment. Some of the most powerful IT firms do not require a degree.
Can I find a job in AI as a new graduate?
According to the report, freshers need to have a fundamental understanding of AI and its applications to compete effectively in the industry. Furthermore, people who can build AI talents might earn extremely high pay and have several career prospects.
How much do AI students make?
In India, the average beginning salary for an AI Engineer is roughly 3.0 Lakhs per year (25.0k per month).
What occupations are most vulnerable to AI?
"Occupations in finance, medicine, and legal activities, which frequently require many years of education and whose core functions rely on accumulated experience to make decisions, may suddenly find themselves at risk of automation from AI," the OECD said.
