Applied Data Science with AI
August 8, 2024 2025-06-03 11:58Applied Data Science with AI
Applied Data Science & AI Program
Our Knowledge Partners, Certification Alliances and Curriculum Creators
Key Highlights of Applied Data Science & AI Certification Program
Why Join Applied Data Science with AI Certification Program ?
Upcoming Batch:-
19th January 2025 (10pm to 1 am )
1st of February 2025 (10 pm to 1 am)
Applied Data Science & AI Certification Program Overview
This Program provides a structured path through the world of artificial intelligence, beginning with Python programming skills and basic statistics. With this bundle, you’ll delve into machine learning, deep learning, computer vision and natural language processing to acquire the tools of this trade. The program also covers reinforcement learning, equipping you to develop AI solutions that learn from interactions. By the end, you’ll have a strong foundation to apply AI technologies in real-world scenarios.
ENROLL NOW & BOOK YOUR SEAT AT FLAT 50% WAIVER ON FEE
Batch Schedule
| Batch | Batch Type |
|---|---|
| Online Live Instructor Led Session | Full-Time |
| Online Live Instructor Led Session | Part-Time |
Regional Timings
| Region | Time |
|---|---|
| IST (India Standard Time) | 09:00 PM – 12:00 AM |
| Bahrain, Qatar, Kuwait, Saudi Arabia | 06:30 PM – 09:30 PM |
| UAE / Oman | 07:30 PM – 09:00 PM |
Talk to our Corporate training advisor
Applied Data Science & AI Certification Program Objectives
This course aims to provide a comprehensive understanding of key AI and ML principles. You will start from Python Programming then go on to statistical methods for data analysis. It enables you to have hands-on experience of machine learning algorithms and go deep for computer vision, natural language processing etc. You will also learn about reinforcement learning which is a subcategory of machine learning that examines how AI agents may improve by just carrying out some actions. It sounds like a lot, but by bringing all of these elements together the course is designed to help you solve hard problems and do serious innovation in AI
Why Learn Applied Data Science & AI Certification Program
?
Program Advantages
Applied Data Science & AI Certification Program Certification
Applied Data Science & AI Certification Program Learning Path/Curriculum
Lecture 01: Introduction to Python, Why Python, Variables, Data Types, Type Casting, Strings, Indexing
Lecture 02: Operators and Conditional Statements, Looping Statements and its Control Statement
Lecture 03: Lambda Functions, *args, **kwargs, Functions
Lecture 04: Data Structures - List, Tuple and List Comprehensions
Lecture 05: Data Structures - Set and Dictionaries
Lecture 06: Classes, Objects and Constructors, Inheritance
Lecture 07: Polymorphism, Abstraction and Encapsulation
Lecture 08: Connecting to Databases, Establishing connections to databases, Executing SQL Queries, ORM (Object-Relational Mapping), Working with NoSQL Databases
Lecture 09: Introduction to Numpy and Pandas
Lecture 10: Introduction to Seaborn and Matplotlib
Lecture 11: Introduction to Statistics, Descriptive Statistics, Sample, Population, Measures of Central Tendency, Standard Deviation
Lecture 12: Variance, Range, IQR, Outliers, Correlation, Covariance, Skewness, Kurtosis, Probability
Lecture 13: Probability, Probability Distributions, Central Limit Theorem, Binomial and Poisson Distribution
Lecture 14: Normal Distribution, Type I & Type II Error
Lecture 15: T-test, Z-test, Hypothesis Testing Interview Questions
Lecture 16: Introduction to ML, Types of Variables, Encoding, Normalization, Standardization, Types of ML, Linear Regression
Lecture 17: Linear Regression, Logistic Regression, SVM, KNN, Naïve Bayes, Decision Tree, Random Forest
Lecture 18: Mean Absolute Error, Mean and Root Mean Square Error, Confusion Matrix, R² Score, Adjusted R² Score, F1 Score
Lecture 19: Classification Report, AUC ROC, Accuracy, Ensemble Techniques, Random Forest, XGBoost
Lecture 20: Unsupervised Machine Learning, PCA, Clustering, k-Means Clustering and Hierarchical Clustering
Lecture 21: Introduction to Neural Network, Forward Propagation, Activation Function
Lecture 22: Activation Functions (Linear, Sigmoid, ReLU, Leaky ReLU), Optimizers, Gradient Descent, Stochastic Gradient Descent
Lecture 23: Mini Batch Gradient Descent, Adagrad, Padding, Pooling, Convolution, Checkpoints and Neural Networks Implementation
Lecture 24: Introduction to Time Series Analysis, Various Components of the TSA, Decomposition Method (Additive Method and Multiplicative)
Lecture 25: ARMA and ARIMA
Lecture 26: Introduction to Image Processing, Feature Detection, OpenCV
Lecture 27: Convolution, Padding, Pooling & its Mechanisms
Lecture 28: Forward Propagation & Backward Propagation for CNN
Lecture 29: CNN Architectures like AlexNet, VGGNet, InceptionNet, ResNet, Transfer Learning
Lecture 30: Introduction to Text Mining, Text Processing using Python and Introduction to NLTK
Lecture 31: Sentiment Analysis, Topic Modeling (LDA) and Named-Entity Recognition
Lecture 32: BERT (Bidirectional Encoder Representations from Transformers), Text Segmentation, Text Mining, Text Classification
Lecture 33: Automatic Speech Recognition, Introduction to Web Scraping
Lecture 34: RL Framework, Components of RL Framework, Examples of Systems
Lecture 35: Types of RL Systems, Q-Learning
Lecture 36: Project Session
Applied Data Science & AI Certification Program Skills Covered
Data Science & AI Certification Program Tools Covered
Applied Data Science & AI Certification Program Benefits
Projects that you will Work On
Job Obligation after this course
We can apply for jobs inÂ
Companies Hiring for this course
Batch Professional Profiles
Program Advisors
IITs
IIMs
NITs
Experts from the IT Industries.
Admission Details
The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.
Course Fees & Financing
Course Fees
(50% OFF upto 31ˢᵗ March)
(Inclusive Of All Taxes)
Payment Partners
We partnered with financing companies to provide competitive finance option at 0% interest rate with no hidden costs
Upcoming Batches/Program Cohorts
| Batch | Date | Time | Batch Type |
|---|---|---|---|
| Online Live Instructor Led Session | 5th April 2025 | 10:00 AM | Full-Time |
| Online Live Instructor Led Session | 29th March 2025 | 02:00 PM | Part-Time |
Comparison with Others
| Feature | Our Applied Data Science & AI Program | Other Applied Data Science & AI Programs |
|---|---|---|
| Curriculum Depth | Comprehensive, covering Python, ML, DL, NLP, CV, and RL | Often focused on basic concepts or specific areas like ML or DL |
| Hands-On Experience | Emphasises practical projects and real-world applications | Varies; may include limited practical exposure |
| Instructor Expertise | Taught by industry professionals and experts | Often led by academic instructors or general trainers |
| Industry-Relevant Skills | Focused on current tools and technologies used in the industry | May include outdated or less industry-relevant content |
| Certification | Provides globally recognized certification | Certification may not be widely recognized |
| Career Support | Includes career services and networking opportunities | Limited or no career support offered |
| Flexibility | Structured yet adaptable learning paths | May have rigid schedules or limited flexibility |
| Learning Resources | Access to extensive resources, including updated materials | Often limited to basic learning materials |
| Project-Based Learning | Strong focus on project-based learning | May include fewer or less challenging projects |
| Job Placement Assistance | Offers job placement assistance and industry connections | Often lacks strong job placement support |
Self Assessments
Applied Data Science & AI Certification Program Training Faqs
An Applied Data Science & AI Certification Program equips learners with key skills in artificial intelligence and machine learning through topics like programming, data handling, and deep learning, offering practical experience and a certification to boost career opportunities.
Joining an AI & ML course helps you gain in-demand skills, stay competitive in a rapidly evolving tech landscape, and unlock career opportunities in fields like data science, AI, and automation. It also provides practical experience, hands-on projects, and certification, enhancing your ability to solve real-world problems using cutting-edge technologies.
Programming syntax, data manipulation, statistical analysis, data visualization, machine learning, deep learning, computer vision techniques, image processing, text processing, sentiment analysis, language modeling, reinforcement learning algorithms
Python /R Programming,Statistics, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Reinforcement Learning
Python, R, Jupyter Notebook/Lab, Anaconda, NumPy, pandas, matplotlib, seaborn, scikit-learn, scipy, statsmodels, matplotlib, seaborn, Excel, scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, matplotlib, seaborn, TensorFlow, Keras, PyTorch, matplotlib, OpenCV, NLTK
A degree in Engineering, Mathematics, Science, or any equivalent field is ideal for pursuing a career in Artificial Intelligence and Data Science.
INR Fees (Exclusive of GST) INR 125,999
INR Fees (Inclusive of GST) INR 148,679.00
USD Fees USD 1499
AI Engineer, Data Scientist, Machine Learning Specialist
Entry-level: 7-12 lakhs per annum
Mid-level: 12-25 lakhs per annum
Senior-level: 25+ lakhs per annum
40+ Projects
1, we will optimise linked in profile and the algorithm of linkedin profile.
2, We will conduct GITHUB and Kaggle sessions.
3,We will do multiple Hackathons and guide you in problem solving skills for the interview process .
4, We will ensure peer learning session are being conducted .
5, We will issue mini certification for every tools.
6,We will asign you a personal mentor on pre booking i’t a one one session.
