COURSE FEATURES
- Duration : Two Months
- Skill level : Basic -Elemetary – Advance – HighTech
- Language : English
- Course Fee: PKR 27,000
- Admission Fee: PKR 2,000
- Examination Fee: PKR 1500
- Assessments: Yes
Employable skills and hands on practice for Artificial Intelligence, including specialization in NLP (Natural Language Processing) or computer vision The objective for delivering the advanced IT curriculum is to impart knowledge and cultivate skills relevant to the field of IT. The course aims to provide participants with a comprehensive understanding of various aspects within the domain, fostering their ability to conduct themselves in a professional and responsible manner. Instructors will deliver technical knowledge and skills necessary for goal-oriented problem-solving, employing practical oriented teaching. Additionally, they will design a practical assessment program aligned with the curriculum’s learning outcomes. Trainees will not only enhance their proficiency in addressing tasks but also develop the capacity to scrutinize issues thoroughly and evaluate opportunities for growth.
By the end of this course, the trainees should gain the following competencies:
• Understanding of core concepts of artificial intelligence and machine learning
• State of the art machine learning techniques
• Hands-on exposure to exploratory data analysis
• Practical exposure to model design, evaluation
• Familiarity with tools and libraries such as scikit learn, pandas numpy, tensorflow, pytorch and keras
• build models which will extract information from image, video & textual data
After the specialization in NLP, student will be comfortable using TensorFlow pipelines for NLP at the end of the course.
Moreover, student will learn
• text processing fundamentals, including text normalization, stemming and lemmatization
• different evaluation metrics for models trained for NLP tasks
• statistical language models like Hidden Markov Model (HMM)
• make a part of speech (POS) tagging model
• named entity recognition
• advanced techniques including word embeddings, deep learning (DL) techniques.
Job Opportunities
AI is the buzzword of the century, attracting attention across industries, motivating changes in products as well as services. It is the very nature of the
subject that makes its applications infinite, in multiple domains. Whether you belong to a technical background or not, chances are that AI can make
your job easier, and push it in the right direction. Dive in to develop an understanding of the core concepts, while gaining hands on experience and
training from the industry’s finest. Trained resources can find work as one of the following roles
• AI Associate Engineer
• Machine Learning associate analyst
• Assistant Data Analyst
• Research Assistant
• Assistant Cyber Security Analyst
• Operating System Security Analys
Companies offering jobs in the respective trade
1. Careem / Ober / Bykea
2. Afiniti
3. CureMD
4. Arbisoft
5. AppsGenni
6. NetSol
7. Systems
8. Fiverivers Technologies
9. confiz
10. Crossover
11. xavor
12. Research institutes
13. All Private Institutes who have an ML departmen
Learning Tools /resources
Following software tools / resources will be used during the course:
1. Python
2. Pycharm
3. Anaconda
4. Matplotlib
5. Jupyter
6. Numpy
7. Pandas
8. OpenCV
9. TensorFlow (maintained by Google)
10. Convolutional Neural Network (CNN or ConvNet)
11. NLTK
Students Feedback
Advance Your Skills with AI Intelligence Course in Lahore
Peak Solutions offers an innovative AI intelligence course in Lahore that will give you the tools you need to succeed in the quickly expanding field of machine learning. Fundamental ideas in deep learning, neural networks, and data analytics are covered in our extensive curriculum. You’ll obtain practical experience that equips you for a range of AI professions through interactive projects and knowledgeable instructors. Our machine learning and AI courses offer the skills and information you need to succeed.
Learn an Artificial Intelligence Course from the Experts
Get the benefits of our Artificial Intelligence Course to explore the world of AI. Anyone interested in learning about the fundamental technologies influencing global industry futures should take this course. Our artificial intelligence course for beginners in Lahore includes fundamental subjects like deep learning, natural language processing, and AI ethics at both the beginning and expert levels. Peak Solutions, an established college in Lahore, is dedicated to giving you an outstanding education that will keep you ahead of technological developments.
Find the Right Path with Ai Courses at Peak Solutions
Explore our extensive selection of AI courses at Peak Solutions in Lahore, each designed to satisfy the various demands of our pupils. We offer the ideal course for everyone, whether you’re a professional trying to advance your knowledge or just starting to enter the world of artificial intelligence. Our courses are meant to give students a strong foundation in the field, together with hands-on training and real-world applications.
Course Features
- Lectures 79
- Quizzes 0
- Duration 216 hours
- Skill level All levels
- Language English
- Students 25
- Assessments Yes
Curriculum
- 12 Sections
- 79 Lessons
- 12 Weeks
- Week 1/12: Starting up with Artificial Intelligence & Basics of Python7
- 1.1Scope and Evolution of Artificial Intelligence1 Week
- 1.2Setting up environment and Leveraging Jupyter Notebook for Seamless and Interactive Data Analysis and Visualization1 Week
- 1.3Embarking on the Journey of Python Mastery1 Week
- 1.4Setting-up python framework, Basic Python Syntax and Structure1 Week
- 1.5Fundamental Data Types (int, float, str, bool), Variables and Assignments1 Week
- 1.6Fundamental mathematics functions in Python {(Addition (+), Subtraction (-), Modulus (%) etc)1 Week
- 1.7Task No. 1 to 6 (Details may be seen in Annexure I)1 Week
- Week 2/12: Conditional statement, Loops, Functions and Data Types5
- 2.1Develop a program incorporating control structures for optimal functionality (IF, IF ELSE, AND ELIF)
- 2.2Orchestration of program using loop structures, String handling and exception handling
- 2.3Formulate program using functions and lists
- 2.4Develop program using tuple, sets and dictionaries
- 2.5Task No. 7 to 14 (Details may be seen in Annexure I)
- Week 3/12: Machine Learning and NumPy Library6
- Week 4/12: Pandas Library5
- 4.1Pandas data structures (series & data frame), Input & output operations using pandas
- 4.2Selection operations, Sort & rank and Retrieving series/ dataframe information
- 4.3Employing Pandas functions, Data alignment
- 4.4Data preprocessing using Pandas
- 4.5Task No. 23 to 28 (Details may be seen in Annexure I)
- Week 5/12: Graphical interpretation of data6
- 5.1Import and install Matplotlib
- 5.2Gearing up the data, Creating the Plot and Plotting routines
- 5.3Customizing the plot, Saving the plot, Displaying the plot
- 5.4Types of plots, Graphs and Search Strategies
- 5.5Brute force search o Depth first search o Breadth first search
- 5.6Task No. 29 to 34 (Details may be seen in Annexure I)
- Week 6/12: Classification and Regression7
- 6.1Disparity between classification and regression
- 6.2Supervised vs. Unsupervised learning
- 6.3Categories of supervised learning
- 6.4Regression () o Univariate linear regression o Multivariate regression
- 6.5Polynomial regression(), Train-Test split and Validation
- 6.6Logistic Regression ()
- 6.7Task No. 35 to 40 (Details may be seen in Annexure I)
- Week 7/12: KNN & Clustering techniques in Machine learning9
- Week 8/12: Dealing with Textual Data6
- Week 9/12: OpenCV (image & video processing)7
- 9.1Preamble to OpenCV, Image installation and importing basic functions of OpenCV
- 9.2Exhibit images in multiple modes & Capture videos using openCV
- 9.3Face detection using OpenCV and Basic operations on images
- 9.4Blend two different images
- 9.5Change fundamental color spaces, Image Thresholding
- 9.6Detect face with mask and without mask
- 9.7Task No. 54 to 60 (Details may be seen in Annexure I)
- Week 10/12: Deep Learning and Neural Networks7
- 10.1Evolution and Importance of Deep Learning and its applications
- 10.2Overview of Neural Networks, Key Terminology: Layers, Nodes, and Weights
- 10.3Understanding Feedforward Neural Networks
- 10.4Convolutional Neural Networks (CNNs)
- 10.5Recurrent Neural Networks (RNNs)
- 10.6Architectural Considerations in Deep Learning
- 10.7Task No. 61 and 65 (Details may be seen in Annexure I)
- Week 11/12: TensorFlow14
- 11.1Preamble & Evolution of TensorFlow
- 11.2Configuring Development Environments & Setting up GPU Support (Optional)
- 11.3Scalar or (0) Dimension Tensor Flow
- 11.4Vectors or 1 Dimension Tensorflow
- 11.5Matrices or (2) Dimension Tensor Flow
- 11.6Building basic computation graph
- 11.7Running basic computational graph
- 11.8Tensor Constant
- 11.9Tensor Placeholder
- 11.10Tensor Variable
- 11.11Padding and how Strides work
- 11.12CNN using Keras in Python on MNIST data set
- 11.13CNN on CIFAR-10 Dataset
- 11.14Task No. 66 to 72
- Week 12/12: Recap of Course & Final Project preparation0
