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Dr. Shikha Awasthi

Sr. Data Scientist

Dr. Shikha is an expert of Artificial Intelligence and developed many projects for top level organizations.


  • Price : Call Now!
  • Lessons : 15
  • Length : 2 Month
  • Level : Advance
  • Category :Science.
  • Started : 15 APR 2024
  • Shift : 02
  • Class : 50

Course Description

Artificial Intelligence is all about human intelligence implemented for computer machines in the form of algorithms. It refers to machine capacity for calculations, estimations, analysis, and reasoning.These capacities can often be modeled in computers, hence becoming “artificial”. language translations, weather analysis, smart cars, smart houses, auto modes in airplanes, auto-driving cars, the auto player mode in various games are the best examples of artificial intelligence.

Machines are learning from their past experience and performing smart work, This is the world of Artificial Intelligence , Market survey shows a huge demand and job openings in artificial intelligence. Our team designed the best program that will guide you in machine learning, deep learning, and Reinforcement Learning.

Some companies have started their journey in AI, others are moving towards it. artificial intelligence is impacting our lives and being used in Manufacturing, Healthcare, Education, and other sectors.

This is the best course to be an AI expert, In this course, you will learn how to create an AI Model using machine learning, neural networks, and TensorFlow, Moreover, you will be an expert on Machine Learning and other AI tools.

At DigiStackEdu, we understand that theory alone isn't enough to be master in Artificial Intelligence. Therefore, we offer a hands-on approach that empowers you to work on real-world AI projects. Under the guidance of our expert and mentors, you'll work on the latest AI tools and technologies, grasping concepts through practical application. This experiential learning allows you to bridge the gap between theory and implementation, preparing you to tackle real challenges with ease.

Through hands-on projects and interactive modules, you'll gain practical experience that sets you apart in the competitive tech landscape. Whether you're a busy professional or a curious beginner, our flexible online platform ensures you can master AI at your own pace. Join the ranks of AI innovators and pioneers today – enroll with DigiStackEdu and become a certified AI expert primed to shape the digital future!

Artificial Intelligence Course eligibility

Artificial Intelligence Course can be opt after 12th and Graduation moreover, anyone can understand AI concepts easily, and if you join training institutes then instructors will help you to update your skills such as Python programming and statistics to learn AI and Machine Learning.

Believe me, nothing is difficult in this world, you just need some great teachers and hands-on experience so that you can easily understand how AI works and how professionals work in companies to build AI-based softwares.

Artificial Intelligence Online Certification

It's time to unlock the all possibilities of the future with the Artificial Intelligence Online Certification Course at Digistackedu. you need to explore the online learning apportunities while diving deep into the world of AI from the comfort of your own space. Our well designed syllabus, led by industry-leading experts, will immerse you in the realms of machine learning, neural networks, and natural language processing.

Learn hands-on projects and interactive AI modules, here you'll gain practical experience that sets you apart in the competitive tech world. Whether you're a busy professional or a curious beginner, our flexible online platform ensures you can master AI at your own pace. Join the ranks of AI innovators and pioneers today – enroll with Digistackedu and become a certified AI expert primed to shape the digital future!

Course Syllabus

Module 1: An Introduction to Artificial Intelligence.

  1. Introduction to Artificial Intelligence.
  2. Background of AI and ML.
  3. Introduction to Reinforcement Learning.
  4. What is Q Learning.
  5. Best Examples of AI.
  6. Introduction to Speech Recognition.
  7. What is Face Detection systems.
  8. Python Essential Libraries for AI.
  1. Introduction to python.
  2. Setting python environment.
  3. installation of anaconda.
  4. Variables,data type and operators in python.
  5. Type casting in Python.
  6. Taking User input Python.
  7. Basic Problem solving skills in python.
  8. Solving Mathmetical equations in Python.
  1. Introduction to Conditional Statements.
  2. Understanding Basics of If and Else.
  3. Controlling the flow of program using IF and Else.
  4. User Input with If-Else
  5. Nesting of If-Else Staements.
  6. Practical Demo on If-Else.
  7. Assignments on If-Else Lecture.
  8. IF and Else with Loop.
  9. Nesting of IF and Else Statements.
  1. Introduction to Loop in Python programming
  2. Basics of for Loop and While Loop.
  3. Combining Loop and If-Else Statements.
  4. Positive and Negative Loop.
  5. Practical on For Loop in Python programming.
  6. Practical on Nested For Loop in Python programming.
  7. Practical on While Loop in Python programming.
  8. Practical on Nested While Loop in Python programming.
  9. For and while Loop on R List.
  10. For and while Loop on R Tuples.
  11. Switch Case Statement in Python Programming.
  1. Introduction to List in Python
  2. List with Loop.
  3. List inside If and Else Statement.
  4. List Append and Extend Function.
  5. Delete Element from Python List.
  6. Update Python List Elements.
  7. Count() function on List.
  8. In and Not in Operators on List.
  9. List in reverse order
  10. Shorting Python List.
  11. Assignments on Python List.
  1. An Introduction to Tuples.
  2. Concept of immutability.
  3. Count Operation on Tuples.
  4. Arithmetic Operators on Tuples.
  5. Checking if two tuples are equal.
  6. Which Operations are Not Allowed on Tuples.
  7. Assignments on Tuples.
  8. Handling duplicates using Python Sets.
  9. Working on Set Constructor.
  1. An Introduction to Dictionaries in Python.
  2. Data Structure of a Dictionary.
  3. adding and removing key value pairs.
  4. updating key value pairs inside a dictionary
  5. Creating dynamic Dictioanries.
  6. Dynamic Dictionary Using functions.
  7. assignments on Python Dictionaries.
  1. An Introduction to Functions in Python.
  2. Creating a First Function.
  3. Function with parameters.
  4. Functions with Return type
  5. Function with Python List and Tuples.
  6. Functions with Python Loop.
  7. Functions for Python Dictionaries.
  8. Python lambda Function.
  9. Assignment on Python Function.
  1. Introduction to Numpy.
  2. Working on NumPy Array.
  3. Arithmetic Operators on Numpy Array.
  4. Inspecting NumPy Array.
  5. Subsetting, Slicing, Indexing on Numpy.
  6. Manipulation on Numpy Array.
  7. Stacking and Splitting Numpy Array.
  8. Aggregate Functions on Numpy Array.
  9. Copying and Sorting Numpy Array.
  10. Introduction to Pandas
  11. Creating DataFrames using Pandas
  12. Reshaping Data – Changing the layout of a data set
  13. Handling Missing values using Pandas
  14. Combining Data Sets using Pandas
  15. Grouping Data uisng Pandas and Pivot Table.
  16. Applying functions on Pandas Data Frame
  17. Plotting Time Series using Pandas
  1. An Introduction to Machine Learning.
  2. Regression vs Classification.
  3. Creating Linear Regression Model .
  4. Creating Logistic Regression Model.
  5. Gradient Decent Algorithm for AI.
  6. Building a Model for Classification.
  7. Evaluting Machine Learning Model Performence.
  1. Introduction to Natural Language Processing.
  2. Working in text.
  3. Word Tokenization in NLP
  4. Text cleaning and transforming
  5. NLTK POS Tagging
  6. NLTK Stemming and Lemmatization
  7. Count Vector for NLP
  8. Latent Semantic Analysis in Python.
  9. Learning TIDIF Vectors in NLP.
  10. Spam Detection using NLP.
  1. An introduction to Neural Network
  2. Understanding working of Neuron
  3. Setting Enviornment for AI.
  4. Working on Convolutional Neural Network.
  5. Understanding Forward Propagation
  6. Feed Forward Artificial Neural Network
  7. Regression using ANN
  8. Activation Functions.
  9. Backpropagation in Neural Network.
  10. Understanding Basics of Tensorflow.
  11. Designing a First Neural Network using Tensorflow.
  12. Working on Layers of Neural Network using Tensorflow.
  13. Image Recognition using Tensorflow.
  14. Working on Recurrent Neural Network using Tensorflow.
  15. RNN for Classification.
  16. CNN for Text Classification.
  1. An Introduction to Reinforcement Learning.
  2. Understanding Agent and Enviornment.
  3. Working on actions in RL.
  4. Designing auto-driver car in AI.
  5. Essential Libraries for RL.
  1. An Introduction to OpenCv.
  2. Installation of OpenCv.
  3. Read and Write Images using OpenCv.
  4. Working on Camera Parameters.
  5. Handling Mouse events using OpenCv.
  6. Image Smoothing and Blending.
  7. Working on Gradients and Edges.
  1. An Introduction to Project Development.
  2. Project Assignments.
  3. Task Allocation and Project guidance.
  4. Final Project Submission.
  1. Introduction to Tableau and Data Visulization.
  2. Tableau architecture.
  3. Intsallation of Tableau Desktop.
  4. Understanding Tableau Interface.
  5. Role of Tableau in Data Science.
  6. Introduction to different types of graphs.
  7. Understanding Tableau Show Me Tab.
  1. Introduction to MySQL.
  2. Understading Tableau Toolbars,Data Pane and Analytics
  3. Tableau and RDBMS connections
  4. Working with Csv file.
  5. Tableau and Excel Connection.
  6. Understanding Tableau Data Source.
  7. Introduction to JSON Files.
  8. Working with JSON file Using Tableau.
  1. Introdutcion to Tableau Fields.
  2. Categorical vs Numerical Columns.
  3. Conversion of fields in Tableau.
  4. Working on Histograms and bar chart.
  5. Working on Time Series chart.
  6. Working on Box Plot in Tableau.
  7. Drawing Pie Chart in Tableau.
  8. Real Time Example of Bubble Chart.
  9. Drawing Scatter Diagram.

Student Reviews

Our Student reviews after completion of this course.

Frequently Asked Questions

Yes, you will get industry valid certificate after completeion of this course and you will be tagged as a AI Expert.
Yes, You can pay your fee in two installments but it depands on the course you selected.
Yes, You can join AI online course even if you do not belong from computer science background. Our experts will help you to upgarde your technical skills, you just need some basic computer skills for this course.
This course is 100% practical oriented, you will work on Machine Learning Models,Tensorflow and Neural Networks to design Artificial Models moreover,after completetion of this course you'll be able to work on python and advance level AI concepts.
DigiStackEdu provide cost effective and quality training,We focus on every student and we understand the value of money.Our Trainers are certified and having more than 10+ years of experience in Digital Marketing, Data Science, Java Programming, Web Designing, Big Data and Data Analytics moreover,We have Trained 47,000+ students and professionals who are working in top level IT companies.
DigiStackEdu only provide internship in Data Science, Digital Marketing, Java Programming, PHP programming and Web Development.For more details please contact to our support team.
Artificial Intelligence is a revolutionary filed, changing world and providing a lot of job opportunties for students and professionals.This is the new era where professionals are making smart cars, smart house,smart bots and smart games.
You can submit your fee after 3 classes, Even after that if you face any issue with in the next 7 days then you can contect to our support team for the return.
This couse is designed to upgrade your skills in Artificial Intelligence and this is the field under development,Companies introducing latest tools and technologies for AI and it might take approx 3 month to understand the conecpt of Artificial Intelligence.