Introduction 

We are surrounded by data, and the importance of data is going to grow rapidly. Data is valuable, but sorting data to extract useful information can be a complicated task. That’s where data science and artificial intelligence come into play. 

From getting show recommendations on Netflix & getting similar product recommendations on various e-commerce platforms to being used in the transportation, healthcare, & automotive industries, data science & AI have made their way into every part of our life. The artificial intelligence market is growing globally and is expected to reach 126 billion dollars by 2025.

That being said, the demand for data science & AI professionals is skyrocketing, so starting a career in this dynamic industry will be a smart decision. In this guide, we’re going to discuss what AI is, how data science & AI are related, skills you’ll need to acquire, the best data science course available on the market, and more. 

Let’s start. 

What is Artificial Intelligence?

Artificial intelligence is a process where you program a computer so that it can make its own decisions. AI is a vast subject. To put it in simple words, AI involves the creation of computer systems that can surpass human intelligence. 

AI’s subset is machine learning. Machine learning is a process that allows you to teach the computer how to learn & study data. This process takes place by allowing the computer to recognize patterns with the help of various examples.

Data science is a vast field that concerns data processes and systems which aim to analyze huge datasets and find meaningful information. The field includes various mathematical and statistical techniques like visualization, multivariate data mining, and data analysis. 

It also includes machine learning and computer science to get relevant information from the data and come up with compelling insights & solutions. 

Artificial intelligence is a process where you make a computer system so intelligent that it can predict the future by analyzing and comparing various datasets. Data science is the underlying logic of artificial intelligence

To understand with an example, let’s think of library software that uses AI. What is the software supposed to do? Its job will be to track the patterns of each user to identify which type of books they love to read to predict what books they’ll be interested to read in the future. So if a user repeatedly reads romance books, the AI software is expected to identify the pattern and recommend similar books to the user. Data science is the art of teaching the system how to identify these patterns. 

How AI should learn & make predictions and what the computer should learn is understood using data science. Data science helps the computer learn how to identify patterns so that AI can further analyze these patterns and make accurate predictions. Thus, AI is a subset of data science.

What Skills Do You Require to Become a Successful AI or Data Science Professional?

Let’s look at the skills you’ll require to become a successful AI or data science professional: 

Programming Skills

For a successful career as an AI professional and to bag the best data science and AI jobs, it is important to have good programming skills. You should be proficient in at least one programming language like Lisp, Java, Python, and C++. Every language is different and fulfills different requirements of artificial intelligence

Statistical Skills

Every algorithm is backed by statistical data. In fact, AI programs made by professionals completely rely on algorithms. And to work your way around algorithms, you need to know algebra, probability, and statistics. Statistical skills also play a significant role in the machine learning process. 

Knowledge of Algorithms

You’ll be considered a good data science or AI engineer if you have ample knowledge related to algorithms. It is vital to know the basics of applied mathematics and everything about algorithms to work effectively. Gradient descent, Convex Optimization, and Quadratic programming are a few areas where applied mathematics and algorithms knowledge is used. 

Natural Language Processing

Natural Language Processing or NLP involves bringing together linguistics, computer science, AI, and information engineering to examine huge data sets. AI professionals usually have to use NLP frequently; thus, it becomes necessary to be skilled in natural language processing. 

Analytical Skills

Data science and AI professionals have to work with data and numbers constantly. It is crucial for an AI professional to have good analytical skills to ensure that they work effectively. Analytical thinking is also important for data science engineers because their job involves asking various questions to check whether the data is correct and discussing the analysis with the organization. 

Business Sense

Business sense is another vital skill for AI engineers. Most AI projects require you to analyze the business and its problems to devise effective measures. To do so, you must have an understanding of how an organization works and its market. Your technical knowledge will be of no use if you fail to translate your vision into a business model. 

How to Pursue AI with a Data Science Course?

If you want to get started with a career in data science and artificial intelligence, IMS Proschool offers three different courses to help you obtain the necessary knowledge and certifications. Let’s look into these courses, their curriculum, and the certifications: 

  1. Certificate in Data Science

The Data Science course offered by IMS Proschool is a 6-month advanced program that prepares you to land impressive data science and AI jobs. The faculty-led training will ensure that you learn advanced data science concepts from industry experts and clear all your doubts quickly. 

The syllabus of this course is completed in two terms which cover multiple topics. 

Term 1 

  • Statistics and statistical methods
  • Python – conditional loops, functions, file input, and output
  • Exploratory analysis – Univariate, Bivariate, Outliers
  • Linear regression – Output interpretation, validation
  • Logical regression – model valuation, confusion matrix
  • Time Series – Forecasting and ARIMA
  • Classification – Decision trees. Random Forest, Assembling
  • Bl and Tableau-Workflows. Visualization, Dashboards
  • SOL – Joins, functions, operators
  • 20 cases studies/projects

Term 2 

  • Regularization Boosting – Hyperparameter Tuning
  • Support Vector Machine – Linear and Non-Linear Classifier
  • Principle Component Analysis (PCA) – Factor Analysis
  • Neural Networks -Tensor Flow, Kera’s, Deep Learning, Neural Networks
  • FRecommendation Systems / NLP – Data Processing, Sentiment Analysis
  • 10 cases studies/projects

After completing this course, you will get the NSE certification and a joint certification from NSDC and IMS Proschool. 

2. PGCM in Data Analytics – AICTE Approved

PGCM (Post Graduation Certificate in Manageemnt) in Data Analytics is a one-year comprehensive program offered by IMS Proschool. The program focuses on making the students proficient in Tensorflow, Power BI, SQL, Tableau, R, and Python, among other programming languages. The classes will focus on analyzing and solving multiple real case studies so that the students learn how to manage and analyze huge sets of data. 

You’ll get complete access to the video content and attend more than 250 hours of live training. Pursuing this course will ensure that you inculcate theoretical knowledge alongside gaining business sense and programming skills. The curriculum of this comprehensive course covers various aspects of data science, including Big Data, artificial intelligence, and machine learning. 

The syllabus of this course will be covered in 2 terms. 

Term 1 

  • Data Analysis in Excel
  • Business Statistics
  • Visualization with PowerBI
  • Introduction to IT Systems
  • Business Communications
  • Marketing Management

Term 2 

  • Data handling with SQL & Python
  • Data Preprocessing & EDA
  • Intro to Machine Learning
  • Machine Learning techniques
  • Advanced Machine Learning
  • Business Simulation

After completing this course, you will receive an AICTE Approved PG certification from AIMA. 

Which industries Offer the best AI Jobs?

Many industries benefit from artificial intelligence and highly demand data science & AI professionals. Following are a few industries that offer the best AI jobs

Banking

The banking sector has started using technology to keep up with market trends and stay up-to-date. The banking sector has adopted AI and ML technologies to shift from keeping records of customers manually to doing the same using technology. 

AI allows banking professionals to store the data efficiently and correctly as huge amounts of data need to be recorded by the banking sector. Adapting to artificial intelligence has helped the sector prevent fraud, offer effective customer support, enhance the quality of data, etc. 

Health Care & Medicine 

The healthcare sector uses artificial intelligence to benefit in multiple ways, like recording data, comparing the diagnosis of different patients with the same disease, treating the patients more effectively, and more. There have been various instances in the medical field where AI has proved to be beneficial for the sector, and it will continue to offer its benefits in the future. Moreover, AI is also used in other healthcare fields such as synthetic biology, drug testing, etc. 

Automotive

Gone are the days when autonomous vehicles only existed in fiction. The future has turned into a reality with the help of artificial intelligence. We have self-driving cars today, which has only been possible because of AI. Studies show that nearly 33 million autonomous vehicles are expected to be sold by 2040

Many companies use data science and AI techniques to manufacture cutting-edge self-driving vehicles. These vehicles collect huge amounts of data daily to ensure efficient routes, impressive safety measures, and effective driving techniques. 

Finance

Artificial intelligence and the finance sector go hand in hand. The finance industry is driven by processing large datasets, accuracy, and consistent data reporting. AI performs these jobs effectively, which is why the financial sector recognizes the significance of data science and AI and uses various AI techniques in its processes. 

For example, many investment platforms have started using Robo-advisors to use AI’s capabilities for creating personalized profiles for investors considering their unique financial goals. 

Transportation & Travel

The transportation & travel industry makes the most use of AI. The industry uses artificial intelligence techniques to suggest the drivers with the best routes and to book vehicles online. 

Data science and AI have made it convenient for users to travel, and using this technology is also profitable for travel companies. These companies capitalize on smartphones with the help of AI. That’s because over 80% of people use smartphones to search for landmarks and local stores. 

One big example of the transportation & travel industry using AI is Google Maps. Google Maps uses artificial intelligence in various ways, which helps the system scan roads, provide traffic updates, and suggest the best routes. On top of that, it can provide information depending upon your mode of transportation, even when you’re on foot. 

E-commerce

E-commerce businesses use artificial intelligence to help improve the customer experience and drive sales. AI is also incorporated in every step of their process to help build strong relationships with their customers and increase the efficiency of other processes. 

E-commerce websites such as Swiggy, Amazon, Zomato, Myntra, etc., are the biggest examples of e-commerce companies incorporating artificial intelligence into their system. Whenever you do anything on these platforms, an algorithm based on artificial intelligence is what helps you take action. 

Job Scopes for AI Professionals 

Artificial intelligence and data science professionals have various job roles. Following are the job scopes for AI professionals: 

Machine Learning Engineer

A Machine Learning Engineer is responsible for ensuring that all the projects related to ML run smoothly. All the aspects of the ML project depend upon the Machine Learning Engineer’s work, and these professionals also need to acquire knowledge of various programming languages alongside AI programming. 

ML engineers work with massive data sets, and they must use their skills to use NLP successfully. As a Machine Learning Engineer, you must also have good analytical skills and be proficient in Java, Python, and Scala. 

Data Scientist

A data scientist’s job involves working with lots of data. Data scientists also constantly use predictive analysis and machine learning to deal with complex and huge datasets. Data scientists are also responsible for developing algorithms to collect and sort the data for practical analysis. 

Data scientists must have knowledge of various platforms and tools like Hadoop, Pig, MapReduce, Spark, etc. To become a skilled data scientist, you must also have good communication skills alongside various critical technical skills. 

Business Intelligence Developer

Business intelligence developers are responsible for analyzing complicated sets of data. Business intelligence developers are data science professionals who understand the business and its market and develop effective measures to boost a company’s revenue. 

You’ll be modeling, creating, and managing datasets as a business intelligence developer. BI developers must also have excellent problem-solving skills to advance in their careers.

Research Scientist

The job of a Research Scientist is highly demanded in the data science and AI field. Research scientists hold expertise in various branches of AI, including machine learning, applied mathematics, deep learning, and computational statistics. To land a good job as a research scientist, you must be experienced in reinforcement learning, NLP, and graphical models. 

Big Data Engineer

Big data engineers are responsible for planning and developing the environment of big data on platforms like Hadoop and Spark. These professionals are also proficient in data visualization, migration, and mining. Moreover, big data engineers must also be skilled in various programming languages like C++, Java, Scala, and Python. 

Conclusion

In today’s technological world, data is our currency. A career in data science and artificial intelligence is growing rapidly, and the demand for professionals in this field is increasing by the day. If you are curious to build a strong career in this field, you should opt for the Data Science or PGCM in Data Analytics courses offered by IMS Proschool. 

Joining any of these courses will accelerate your job prospects and help you create a lucrative career for yourself. These certificate courses will help you kick start your career in this field or advance in your career as a data science professional.

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